Dropout_Regularization_in_Keras.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Dropout Regularization in Keras.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KhS1bnqe32Gc"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropout Regularization For Neural Networks"
      ],
      "metadata": {
        "id": "U_Ylmy0833Vw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dropout is a regularization technique for neural network models proposed by Srivastava, et al. in their 2014 paper Dropout: A Simple Way to Prevent Neural Networks from Overfitting (download the PDF).\n",
        "\n"
      ],
      "metadata": {
        "id": "wGp2JY8A35QK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dropout is a technique where randomly selected neurons are ignored during training. They are “dropped-out” randomly. This means that their contribution to the activation of downstream neurons is temporally removed on the forward pass and any weight updates are not applied to the neuron on the backward pass."
      ],
      "metadata": {
        "id": "QZIARV3c3_Sx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "After completing this tutorial, you will know:\n",
        "\n",
        "1. How to create a dropout layer using the Keras API.\n",
        "\n",
        "2. How to add dropout regularization to MLP, CNN, and RNN layers using the Keras API.\n",
        "\n",
        "3. How to reduce overfitting by adding a dropout regularization to an existing model."
      ],
      "metadata": {
        "id": "AVY3XkzA4UG1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Tutorial Overview\n",
        "This tutorial is divided into three parts; they are:\n",
        "\n",
        "1. Dropout Regularization in Keras\n",
        "\n",
        "2. Dropout Regularization on Layers\n",
        "\n",
        "3. Dropout Regularization Case Study"
      ],
      "metadata": {
        "id": "W-BEMVzL4uci"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropout Regularization in Keras"
      ],
      "metadata": {
        "id": "9ly7Q0n35DWT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Keras supports dropout regularization.\n",
        "\n",
        "2. The simplest form of dropout in Keras is provided by a Dropout core layer.\n",
        "\n",
        "3. When created, the dropout rate can be specified to the layer as the probability of setting each input to the layer to zero. This is different from the definition of dropout rate from the papers, in which the rate refers to the probability of retaining an input.\n",
        "\n",
        "4. Therefore, when a dropout rate of 0.8 is suggested in a paper (retain 80%), this will, in fact, will be a dropout rate of 0.2 (set 20% of inputs to zero).\n",
        "\n",
        "5. Below is an example of creating a dropout layer with a 50% chance of setting inputs to zero.\n",
        "\n",
        "layer = Dropout(0.5)"
      ],
      "metadata": {
        "id": "sdW4fK3n5HNP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropout Regularization on Layers"
      ],
      "metadata": {
        "id": "1Ts5kZni5RPd"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The Dropout layer is added to a model between existing layers and applies to outputs of the prior layer that are fed to the subsequent layer.\n",
        "\n",
        "For example, given two dense layers:\n",
        "\n",
        "...\n",
        "\n",
        "model.append(Dense(32))\n",
        "\n",
        "model.append(Dense(32))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "PpEYRN-P5Voe"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "We can insert a dropout layer between them, in which case the outputs or activations of the first layer have dropout applied to them, which are then taken as input to the next layer.\n",
        "\n",
        "It is this second layer now which has dropout applied.\n",
        "\n",
        "...\n",
        "\n",
        "model.append(Dense(32))\n",
        "\n",
        "model.append(Dropout(0.5))\n",
        "\n",
        "model.append(Dense(32))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "bPnw_Yw75e1j"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dropout can also be applied to the visible layer, e.g. the inputs to the network.\n",
        "\n",
        "This requires that you define the network with the Dropout layer as the first layer and add the input_shape argument to the layer to specify the expected shape of the input samples."
      ],
      "metadata": {
        "id": "S5Vv0PxB5mZT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "...\n",
        "model.add(Dropout(0.5, input_shape=(2,)))\n",
        "..."
      ],
      "metadata": {
        "id": "LiSG0_5H5ofo"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# MLP Dropout Regularization"
      ],
      "metadata": {
        "id": "74HGqHcd5r__"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The example below adds dropout between two dense fully connected layers."
      ],
      "metadata": {
        "id": "z4xBmpT65xau"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of dropout between fully connected layers\n",
        "from keras.layers import Dense\n",
        "from keras.layers import Dropout\n",
        "...\n",
        "\n",
        "model.add(Dense(32))\n",
        "\n",
        "model.add(Dropout(0.5))\n",
        "\n",
        "model.add(Dense(1))\n",
        "..."
      ],
      "metadata": {
        "id": "_KmVRBPq5zzv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# CNN Dropout Regularization"
      ],
      "metadata": {
        "id": "n-lt7Xeu566s"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dropout can be used after convolutional layers (e.g. Conv2D) and after pooling layers (e.g. MaxPooling2D).\n",
        "\n",
        "Often, dropout is only used after the pooling layers, but this is just a rough heuristic."
      ],
      "metadata": {
        "id": "BUvfcDrF5-qA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of dropout for a CNN\n",
        "\n",
        "from keras.layers import Dense\n",
        "\n",
        "from keras.layers import Conv2D\n",
        "\n",
        "from keras.layers import MaxPooling2D\n",
        "\n",
        "from keras.layers import Dropout\n",
        "\n",
        "...\n",
        "\n",
        "model.add(Conv2D(32, (3,3)))\n",
        "\n",
        "model.add(Conv2D(32, (3,3)))\n",
        "\n",
        "model.add(MaxPooling2D())\n",
        "\n",
        "model.add(Dropout(0.5))\n",
        "\n",
        "model.add(Dense(1))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "V6jII1u76Be5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this case, dropout is applied to each element or cell within the feature maps.\n",
        "\n",
        "An alternative way to use dropout with convolutional neural networks is to dropout entire feature maps from the convolutional layer which are then not used during pooling. This is called spatial dropout (or “SpatialDropout“)."
      ],
      "metadata": {
        "id": "Fdq8N6qm6Ppm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Spatial Dropout is provided in Keras via the SpatialDropout2D layer (as well as 1D and 3D versions)."
      ],
      "metadata": {
        "id": "5IBat08f6S1N"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of spatial dropout for a CNN\n",
        "\n",
        "from keras.layers import Dense\n",
        "\n",
        "from keras.layers import Conv2D\n",
        "\n",
        "from keras.layers import MaxPooling2D\n",
        "\n",
        "from keras.layers import SpatialDropout2D\n",
        "\n",
        "...\n",
        "\n",
        "model.add(Conv2D(32, (3,3)))\n",
        "\n",
        "model.add(Conv2D(32, (3,3)))\n",
        "\n",
        "model.add(SpatialDropout2D(0.5))\n",
        "\n",
        "model.add(MaxPooling2D())\n",
        "\n",
        "model.add(Dense(1))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "ue7fhZSP6V2m"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# RNN Dropout Regularization"
      ],
      "metadata": {
        "id": "iEep6rEw6ff7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The example below adds dropout between two layers: an LSTM recurrent layer and a dense fully connected layers."
      ],
      "metadata": {
        "id": "_sSx9EVS6jxu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of dropout between LSTM and fully connected layers\n",
        "\n",
        "from keras.layers import Dense\n",
        "\n",
        "from keras.layers import LSTM\n",
        "\n",
        "from keras.layers import Dropout\n",
        "\n",
        "...\n",
        "\n",
        "model.add(LSTM(32))\n",
        "\n",
        "model.add(Dropout(0.5))\n",
        "\n",
        "model.add(Dense(1))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "F3vP_u286m3P"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "This example applies dropout to, in this case, 32 outputs from the LSTM layer provided as input to the Dense layer.\n",
        "\n",
        "Alternately, the inputs to the LSTM may be subjected to dropout. In this case, a different dropout mask is applied to each time step within each sample presented to the LSTM."
      ],
      "metadata": {
        "id": "1FX8gxUQ65f2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of dropout before LSTM layer\n",
        "\n",
        "from keras.layers import Dense\n",
        "\n",
        "from keras.layers import LSTM\n",
        "\n",
        "from keras.layers import Dropout\n",
        "\n",
        "...\n",
        "\n",
        "model.add(Dropout(0.5, input_shape=(...)))\n",
        "\n",
        "model.add(LSTM(32))\n",
        "\n",
        "model.add(Dense(1))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "Uw9O0Gy368Jq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Keras supports Variational RNNs (i.e. consistent dropout across the time steps of a sample for inputs and recurrent inputs) via two arguments on the recurrent layers, namely “dropout” for inputs and “recurrent_dropout” for recurrent inputs."
      ],
      "metadata": {
        "id": "kdVWqPLN7B9m"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# example of variational LSTM dropout\n",
        "\n",
        "from keras.layers import Dense\n",
        "\n",
        "from keras.layers import LSTM\n",
        "\n",
        "from keras.layers import Dropout\n",
        "\n",
        "...\n",
        "\n",
        "model.add(LSTM(32, dropout=0.5, recurrent_dropout=0.5))\n",
        "\n",
        "model.add(Dense(1))\n",
        "\n",
        "..."
      ],
      "metadata": {
        "id": "UWnzoU667Duc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dropout Regularization Case Study"
      ],
      "metadata": {
        "id": "Zpf2mwve7JQh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Binary Classification Problem\n",
        "We will use a standard binary classification problem that defines two two-dimensional concentric circles of observations, one circle for each class.\n",
        "\n",
        "Each observation has two input variables with the same scale and a class output value of either 0 or 1. This dataset is called the “circles” dataset because of the shape of the observations in each class when plotted.\n",
        "\n",
        "We can use the make_circles() function to generate observations from this problem. We will add noise to the data and seed the random number generator so that the same samples are generated each time the code is run."
      ],
      "metadata": {
        "id": "khFYipyk7Or4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# generate two circles dataset\n",
        "from sklearn.datasets import make_circles\n",
        "from matplotlib import pyplot\n",
        "from pandas import DataFrame\n",
        "# scatter plot of the circles dataset with points colored by class\n",
        "from sklearn.datasets import make_circles\n",
        "from numpy import where\n",
        "from keras.models import Sequential\n",
        "from tensorflow.keras.optimizers import SGD\n",
        "# example of batch normalization for an mlp\n",
        "from keras.layers import Dense\n",
        "from keras.layers import BatchNormalization,Activation,Dropout\n",
        "from matplotlib import pyplot\n"
      ],
      "metadata": {
        "id": "PdYow6-W34pm"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# generate 2d classification dataset\n",
        "X, y = make_circles(n_samples=100, noise=0.1, random_state=1)\n"
      ],
      "metadata": {
        "id": "GisnwDJ77VDF"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot, dots colored by class value\n",
        "df = DataFrame(dict(x=X[:,0], y=X[:,1], label=y))\n"
      ],
      "metadata": {
        "id": "LlXBlR5y7XT3"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "colors = {0:'red', 1:'blue'}\n",
        "fig, ax = pyplot.subplots()\n",
        "grouped = df.groupby('label')\n",
        "for key, group in grouped:\n",
        "    group.plot(ax=ax, kind='scatter', x='x', y='y', label=key, color=colors[key])\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "tDud6Kb07Yvs",
        "outputId": "2cb710f6-e3e6-41e1-8809-bbb42573fd29"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Overfit Multilayer Perceptron"
      ],
      "metadata": {
        "id": "ZjNBoZ1E79-K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# generate 2d classification dataset\n",
        "X, y = make_circles(n_samples=100, noise=0.1, random_state=1)\n"
      ],
      "metadata": {
        "id": "rzbSn6657ZLL"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# split into train and test\n",
        "n_train = 30\n",
        "trainX, testX = X[:n_train, :], X[n_train:, :]\n",
        "trainy, testy = y[:n_train], y[n_train:]"
      ],
      "metadata": {
        "id": "gugsAjoe8eMa"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next, we can define the model.\n",
        "\n",
        "The hidden layer uses 500 nodes in the hidden layer and the rectified linear activation function. A sigmoid activation function is used in the output layer in order to predict class values of 0 or 1.\n",
        "\n",
        "The model is optimized using the binary cross entropy loss function, suitable for binary classification problems and the efficient Adam version of gradient descent."
      ],
      "metadata": {
        "id": "s7pdJ6Bn8ihf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        ""
      ],
      "metadata": {
        "id": "LA5se7hT8ilP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# define model\n",
        "model = Sequential()\n",
        "model.add(Dense(500, input_dim=2, activation='relu'))\n",
        "model.add(Dense(1, activation='sigmoid'))\n",
        "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "Rd5dcJoF8e1g"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# fit model\n",
        "history = model.fit(trainX, trainy, validation_data=(testX, testy), epochs=4000, verbose=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hh-YuVqd8mCn",
        "outputId": "4c2e567d-9f7e-44be-91f5-8989ee2bd214"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0324 - accuracy: 1.0000 - val_loss: 0.9314 - val_accuracy: 0.7857\n",
            "Epoch 1502/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0323 - accuracy: 1.0000 - val_loss: 0.9322 - val_accuracy: 0.7857\n",
            "Epoch 1503/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0323 - accuracy: 1.0000 - val_loss: 0.9330 - val_accuracy: 0.7857\n",
            "Epoch 1504/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0322 - accuracy: 1.0000 - val_loss: 0.9338 - val_accuracy: 0.7857\n",
            "Epoch 1505/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0322 - accuracy: 1.0000 - val_loss: 0.9345 - val_accuracy: 0.7857\n",
            "Epoch 1506/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0321 - accuracy: 1.0000 - val_loss: 0.9351 - val_accuracy: 0.7857\n",
            "Epoch 1507/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0321 - accuracy: 1.0000 - val_loss: 0.9356 - val_accuracy: 0.7857\n",
            "Epoch 1508/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0320 - accuracy: 1.0000 - val_loss: 0.9362 - val_accuracy: 0.7857\n",
            "Epoch 1509/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0319 - accuracy: 1.0000 - val_loss: 0.9368 - val_accuracy: 0.7857\n",
            "Epoch 1510/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0319 - accuracy: 1.0000 - val_loss: 0.9374 - val_accuracy: 0.7857\n",
            "Epoch 1511/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0318 - accuracy: 1.0000 - val_loss: 0.9382 - val_accuracy: 0.7857\n",
            "Epoch 1512/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0318 - accuracy: 1.0000 - val_loss: 0.9390 - val_accuracy: 0.7857\n",
            "Epoch 1513/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0317 - accuracy: 1.0000 - val_loss: 0.9399 - val_accuracy: 0.7857\n",
            "Epoch 1514/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0317 - accuracy: 1.0000 - val_loss: 0.9408 - val_accuracy: 0.7857\n",
            "Epoch 1515/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0316 - accuracy: 1.0000 - val_loss: 0.9416 - val_accuracy: 0.7857\n",
            "Epoch 1516/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0316 - accuracy: 1.0000 - val_loss: 0.9423 - val_accuracy: 0.7857\n",
            "Epoch 1517/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0315 - accuracy: 1.0000 - val_loss: 0.9428 - val_accuracy: 0.7857\n",
            "Epoch 1518/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0315 - accuracy: 1.0000 - val_loss: 0.9435 - val_accuracy: 0.7857\n",
            "Epoch 1519/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0314 - accuracy: 1.0000 - val_loss: 0.9442 - val_accuracy: 0.7857\n",
            "Epoch 1520/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0313 - accuracy: 1.0000 - val_loss: 0.9448 - val_accuracy: 0.7857\n",
            "Epoch 1521/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0313 - accuracy: 1.0000 - val_loss: 0.9454 - val_accuracy: 0.7857\n",
            "Epoch 1522/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0312 - accuracy: 1.0000 - val_loss: 0.9460 - val_accuracy: 0.7857\n",
            "Epoch 1523/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0312 - accuracy: 1.0000 - val_loss: 0.9467 - val_accuracy: 0.7857\n",
            "Epoch 1524/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0311 - accuracy: 1.0000 - val_loss: 0.9475 - val_accuracy: 0.7857\n",
            "Epoch 1525/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0311 - accuracy: 1.0000 - val_loss: 0.9483 - val_accuracy: 0.7857\n",
            "Epoch 1526/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0310 - accuracy: 1.0000 - val_loss: 0.9490 - val_accuracy: 0.7857\n",
            "Epoch 1527/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0310 - accuracy: 1.0000 - val_loss: 0.9497 - val_accuracy: 0.7857\n",
            "Epoch 1528/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0309 - accuracy: 1.0000 - val_loss: 0.9504 - val_accuracy: 0.7857\n",
            "Epoch 1529/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0309 - accuracy: 1.0000 - val_loss: 0.9512 - val_accuracy: 0.7857\n",
            "Epoch 1530/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0308 - accuracy: 1.0000 - val_loss: 0.9519 - val_accuracy: 0.7857\n",
            "Epoch 1531/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0308 - accuracy: 1.0000 - val_loss: 0.9525 - val_accuracy: 0.7857\n",
            "Epoch 1532/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0307 - accuracy: 1.0000 - val_loss: 0.9531 - val_accuracy: 0.7857\n",
            "Epoch 1533/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0307 - accuracy: 1.0000 - val_loss: 0.9538 - val_accuracy: 0.7857\n",
            "Epoch 1534/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0306 - accuracy: 1.0000 - val_loss: 0.9546 - val_accuracy: 0.7857\n",
            "Epoch 1535/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0306 - accuracy: 1.0000 - val_loss: 0.9554 - val_accuracy: 0.7857\n",
            "Epoch 1536/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0305 - accuracy: 1.0000 - val_loss: 0.9562 - val_accuracy: 0.7857\n",
            "Epoch 1537/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0305 - accuracy: 1.0000 - val_loss: 0.9568 - val_accuracy: 0.7857\n",
            "Epoch 1538/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0304 - accuracy: 1.0000 - val_loss: 0.9574 - val_accuracy: 0.7857\n",
            "Epoch 1539/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0304 - accuracy: 1.0000 - val_loss: 0.9580 - val_accuracy: 0.7857\n",
            "Epoch 1540/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0303 - accuracy: 1.0000 - val_loss: 0.9586 - val_accuracy: 0.7857\n",
            "Epoch 1541/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0302 - accuracy: 1.0000 - val_loss: 0.9593 - val_accuracy: 0.7857\n",
            "Epoch 1542/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0302 - accuracy: 1.0000 - val_loss: 0.9600 - val_accuracy: 0.7857\n",
            "Epoch 1543/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0301 - accuracy: 1.0000 - val_loss: 0.9607 - val_accuracy: 0.7857\n",
            "Epoch 1544/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0301 - accuracy: 1.0000 - val_loss: 0.9614 - val_accuracy: 0.7857\n",
            "Epoch 1545/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0300 - accuracy: 1.0000 - val_loss: 0.9623 - val_accuracy: 0.7857\n",
            "Epoch 1546/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0300 - accuracy: 1.0000 - val_loss: 0.9630 - val_accuracy: 0.7857\n",
            "Epoch 1547/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0299 - accuracy: 1.0000 - val_loss: 0.9638 - val_accuracy: 0.7857\n",
            "Epoch 1548/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0299 - accuracy: 1.0000 - val_loss: 0.9644 - val_accuracy: 0.7857\n",
            "Epoch 1549/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0298 - accuracy: 1.0000 - val_loss: 0.9649 - val_accuracy: 0.7857\n",
            "Epoch 1550/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0298 - accuracy: 1.0000 - val_loss: 0.9655 - val_accuracy: 0.7857\n",
            "Epoch 1551/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0297 - accuracy: 1.0000 - val_loss: 0.9661 - val_accuracy: 0.7857\n",
            "Epoch 1552/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0297 - accuracy: 1.0000 - val_loss: 0.9666 - val_accuracy: 0.7857\n",
            "Epoch 1553/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0296 - accuracy: 1.0000 - val_loss: 0.9673 - val_accuracy: 0.7857\n",
            "Epoch 1554/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0296 - accuracy: 1.0000 - val_loss: 0.9682 - val_accuracy: 0.7857\n",
            "Epoch 1555/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0295 - accuracy: 1.0000 - val_loss: 0.9691 - val_accuracy: 0.7857\n",
            "Epoch 1556/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0295 - accuracy: 1.0000 - val_loss: 0.9698 - val_accuracy: 0.7857\n",
            "Epoch 1557/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0294 - accuracy: 1.0000 - val_loss: 0.9705 - val_accuracy: 0.7857\n",
            "Epoch 1558/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0294 - accuracy: 1.0000 - val_loss: 0.9711 - val_accuracy: 0.7857\n",
            "Epoch 1559/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0293 - accuracy: 1.0000 - val_loss: 0.9719 - val_accuracy: 0.7857\n",
            "Epoch 1560/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0293 - accuracy: 1.0000 - val_loss: 0.9725 - val_accuracy: 0.7857\n",
            "Epoch 1561/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0292 - accuracy: 1.0000 - val_loss: 0.9731 - val_accuracy: 0.7857\n",
            "Epoch 1562/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0292 - accuracy: 1.0000 - val_loss: 0.9737 - val_accuracy: 0.7857\n",
            "Epoch 1563/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0291 - accuracy: 1.0000 - val_loss: 0.9744 - val_accuracy: 0.7857\n",
            "Epoch 1564/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0291 - accuracy: 1.0000 - val_loss: 0.9751 - val_accuracy: 0.7857\n",
            "Epoch 1565/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0290 - accuracy: 1.0000 - val_loss: 0.9758 - val_accuracy: 0.7857\n",
            "Epoch 1566/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0290 - accuracy: 1.0000 - val_loss: 0.9765 - val_accuracy: 0.7857\n",
            "Epoch 1567/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0289 - accuracy: 1.0000 - val_loss: 0.9772 - val_accuracy: 0.7857\n",
            "Epoch 1568/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0289 - accuracy: 1.0000 - val_loss: 0.9779 - val_accuracy: 0.7857\n",
            "Epoch 1569/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0289 - accuracy: 1.0000 - val_loss: 0.9786 - val_accuracy: 0.7857\n",
            "Epoch 1570/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0288 - accuracy: 1.0000 - val_loss: 0.9794 - val_accuracy: 0.7857\n",
            "Epoch 1571/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0288 - accuracy: 1.0000 - val_loss: 0.9800 - val_accuracy: 0.7857\n",
            "Epoch 1572/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0287 - accuracy: 1.0000 - val_loss: 0.9807 - val_accuracy: 0.7857\n",
            "Epoch 1573/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0287 - accuracy: 1.0000 - val_loss: 0.9814 - val_accuracy: 0.7857\n",
            "Epoch 1574/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0286 - accuracy: 1.0000 - val_loss: 0.9821 - val_accuracy: 0.7857\n",
            "Epoch 1575/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0286 - accuracy: 1.0000 - val_loss: 0.9827 - val_accuracy: 0.7857\n",
            "Epoch 1576/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0285 - accuracy: 1.0000 - val_loss: 0.9834 - val_accuracy: 0.7857\n",
            "Epoch 1577/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0285 - accuracy: 1.0000 - val_loss: 0.9841 - val_accuracy: 0.7857\n",
            "Epoch 1578/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0284 - accuracy: 1.0000 - val_loss: 0.9849 - val_accuracy: 0.7857\n",
            "Epoch 1579/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0284 - accuracy: 1.0000 - val_loss: 0.9855 - val_accuracy: 0.7857\n",
            "Epoch 1580/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0283 - accuracy: 1.0000 - val_loss: 0.9860 - val_accuracy: 0.7857\n",
            "Epoch 1581/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0283 - accuracy: 1.0000 - val_loss: 0.9867 - val_accuracy: 0.7857\n",
            "Epoch 1582/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0282 - accuracy: 1.0000 - val_loss: 0.9874 - val_accuracy: 0.7857\n",
            "Epoch 1583/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0282 - accuracy: 1.0000 - val_loss: 0.9881 - val_accuracy: 0.7857\n",
            "Epoch 1584/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0281 - accuracy: 1.0000 - val_loss: 0.9888 - val_accuracy: 0.7857\n",
            "Epoch 1585/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0281 - accuracy: 1.0000 - val_loss: 0.9894 - val_accuracy: 0.7857\n",
            "Epoch 1586/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0280 - accuracy: 1.0000 - val_loss: 0.9902 - val_accuracy: 0.7857\n",
            "Epoch 1587/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0280 - accuracy: 1.0000 - val_loss: 0.9910 - val_accuracy: 0.7857\n",
            "Epoch 1588/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0279 - accuracy: 1.0000 - val_loss: 0.9917 - val_accuracy: 0.7857\n",
            "Epoch 1589/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0279 - accuracy: 1.0000 - val_loss: 0.9922 - val_accuracy: 0.7857\n",
            "Epoch 1590/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0278 - accuracy: 1.0000 - val_loss: 0.9928 - val_accuracy: 0.7857\n",
            "Epoch 1591/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0278 - accuracy: 1.0000 - val_loss: 0.9934 - val_accuracy: 0.7857\n",
            "Epoch 1592/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0278 - accuracy: 1.0000 - val_loss: 0.9942 - val_accuracy: 0.7857\n",
            "Epoch 1593/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0277 - accuracy: 1.0000 - val_loss: 0.9948 - val_accuracy: 0.7857\n",
            "Epoch 1594/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0277 - accuracy: 1.0000 - val_loss: 0.9956 - val_accuracy: 0.7857\n",
            "Epoch 1595/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0276 - accuracy: 1.0000 - val_loss: 0.9963 - val_accuracy: 0.7857\n",
            "Epoch 1596/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0276 - accuracy: 1.0000 - val_loss: 0.9970 - val_accuracy: 0.7857\n",
            "Epoch 1597/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0275 - accuracy: 1.0000 - val_loss: 0.9977 - val_accuracy: 0.7857\n",
            "Epoch 1598/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0275 - accuracy: 1.0000 - val_loss: 0.9983 - val_accuracy: 0.7857\n",
            "Epoch 1599/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0274 - accuracy: 1.0000 - val_loss: 0.9988 - val_accuracy: 0.7857\n",
            "Epoch 1600/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0274 - accuracy: 1.0000 - val_loss: 0.9993 - val_accuracy: 0.7857\n",
            "Epoch 1601/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0273 - accuracy: 1.0000 - val_loss: 1.0000 - val_accuracy: 0.7857\n",
            "Epoch 1602/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0273 - accuracy: 1.0000 - val_loss: 1.0008 - val_accuracy: 0.7857\n",
            "Epoch 1603/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0272 - accuracy: 1.0000 - val_loss: 1.0014 - val_accuracy: 0.7857\n",
            "Epoch 1604/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0272 - accuracy: 1.0000 - val_loss: 1.0021 - val_accuracy: 0.7857\n",
            "Epoch 1605/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0272 - accuracy: 1.0000 - val_loss: 1.0028 - val_accuracy: 0.7857\n",
            "Epoch 1606/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0271 - accuracy: 1.0000 - val_loss: 1.0037 - val_accuracy: 0.7857\n",
            "Epoch 1607/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0271 - accuracy: 1.0000 - val_loss: 1.0045 - val_accuracy: 0.7857\n",
            "Epoch 1608/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0270 - accuracy: 1.0000 - val_loss: 1.0052 - val_accuracy: 0.7857\n",
            "Epoch 1609/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0270 - accuracy: 1.0000 - val_loss: 1.0058 - val_accuracy: 0.7857\n",
            "Epoch 1610/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0269 - accuracy: 1.0000 - val_loss: 1.0064 - val_accuracy: 0.7857\n",
            "Epoch 1611/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0269 - accuracy: 1.0000 - val_loss: 1.0071 - val_accuracy: 0.7857\n",
            "Epoch 1612/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0268 - accuracy: 1.0000 - val_loss: 1.0078 - val_accuracy: 0.7857\n",
            "Epoch 1613/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0268 - accuracy: 1.0000 - val_loss: 1.0085 - val_accuracy: 0.7857\n",
            "Epoch 1614/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0267 - accuracy: 1.0000 - val_loss: 1.0090 - val_accuracy: 0.7857\n",
            "Epoch 1615/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0267 - accuracy: 1.0000 - val_loss: 1.0094 - val_accuracy: 0.7857\n",
            "Epoch 1616/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0267 - accuracy: 1.0000 - val_loss: 1.0102 - val_accuracy: 0.7857\n",
            "Epoch 1617/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0266 - accuracy: 1.0000 - val_loss: 1.0110 - val_accuracy: 0.7857\n",
            "Epoch 1618/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0266 - accuracy: 1.0000 - val_loss: 1.0117 - val_accuracy: 0.7857\n",
            "Epoch 1619/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0265 - accuracy: 1.0000 - val_loss: 1.0123 - val_accuracy: 0.7857\n",
            "Epoch 1620/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0265 - accuracy: 1.0000 - val_loss: 1.0128 - val_accuracy: 0.7857\n",
            "Epoch 1621/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0264 - accuracy: 1.0000 - val_loss: 1.0135 - val_accuracy: 0.7857\n",
            "Epoch 1622/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0264 - accuracy: 1.0000 - val_loss: 1.0142 - val_accuracy: 0.7857\n",
            "Epoch 1623/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0263 - accuracy: 1.0000 - val_loss: 1.0149 - val_accuracy: 0.7857\n",
            "Epoch 1624/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0263 - accuracy: 1.0000 - val_loss: 1.0154 - val_accuracy: 0.7857\n",
            "Epoch 1625/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0263 - accuracy: 1.0000 - val_loss: 1.0160 - val_accuracy: 0.7857\n",
            "Epoch 1626/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0262 - accuracy: 1.0000 - val_loss: 1.0168 - val_accuracy: 0.7857\n",
            "Epoch 1627/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0262 - accuracy: 1.0000 - val_loss: 1.0175 - val_accuracy: 0.7857\n",
            "Epoch 1628/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0261 - accuracy: 1.0000 - val_loss: 1.0183 - val_accuracy: 0.7857\n",
            "Epoch 1629/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0261 - accuracy: 1.0000 - val_loss: 1.0190 - val_accuracy: 0.7857\n",
            "Epoch 1630/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0261 - accuracy: 1.0000 - val_loss: 1.0195 - val_accuracy: 0.7857\n",
            "Epoch 1631/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0260 - accuracy: 1.0000 - val_loss: 1.0201 - val_accuracy: 0.7857\n",
            "Epoch 1632/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0260 - accuracy: 1.0000 - val_loss: 1.0208 - val_accuracy: 0.7857\n",
            "Epoch 1633/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0259 - accuracy: 1.0000 - val_loss: 1.0214 - val_accuracy: 0.7857\n",
            "Epoch 1634/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0259 - accuracy: 1.0000 - val_loss: 1.0221 - val_accuracy: 0.7857\n",
            "Epoch 1635/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0258 - accuracy: 1.0000 - val_loss: 1.0229 - val_accuracy: 0.7857\n",
            "Epoch 1636/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0258 - accuracy: 1.0000 - val_loss: 1.0235 - val_accuracy: 0.7857\n",
            "Epoch 1637/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0258 - accuracy: 1.0000 - val_loss: 1.0242 - val_accuracy: 0.7857\n",
            "Epoch 1638/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0257 - accuracy: 1.0000 - val_loss: 1.0249 - val_accuracy: 0.7857\n",
            "Epoch 1639/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0257 - accuracy: 1.0000 - val_loss: 1.0255 - val_accuracy: 0.7857\n",
            "Epoch 1640/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0256 - accuracy: 1.0000 - val_loss: 1.0261 - val_accuracy: 0.7857\n",
            "Epoch 1641/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0256 - accuracy: 1.0000 - val_loss: 1.0267 - val_accuracy: 0.7857\n",
            "Epoch 1642/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0255 - accuracy: 1.0000 - val_loss: 1.0272 - val_accuracy: 0.7857\n",
            "Epoch 1643/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0255 - accuracy: 1.0000 - val_loss: 1.0280 - val_accuracy: 0.7857\n",
            "Epoch 1644/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0255 - accuracy: 1.0000 - val_loss: 1.0287 - val_accuracy: 0.7857\n",
            "Epoch 1645/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0254 - accuracy: 1.0000 - val_loss: 1.0294 - val_accuracy: 0.7857\n",
            "Epoch 1646/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0254 - accuracy: 1.0000 - val_loss: 1.0301 - val_accuracy: 0.7857\n",
            "Epoch 1647/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0253 - accuracy: 1.0000 - val_loss: 1.0307 - val_accuracy: 0.7857\n",
            "Epoch 1648/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0253 - accuracy: 1.0000 - val_loss: 1.0314 - val_accuracy: 0.7857\n",
            "Epoch 1649/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0252 - accuracy: 1.0000 - val_loss: 1.0321 - val_accuracy: 0.7857\n",
            "Epoch 1650/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0252 - accuracy: 1.0000 - val_loss: 1.0327 - val_accuracy: 0.7857\n",
            "Epoch 1651/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0252 - accuracy: 1.0000 - val_loss: 1.0333 - val_accuracy: 0.7857\n",
            "Epoch 1652/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0251 - accuracy: 1.0000 - val_loss: 1.0338 - val_accuracy: 0.7857\n",
            "Epoch 1653/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0251 - accuracy: 1.0000 - val_loss: 1.0343 - val_accuracy: 0.7857\n",
            "Epoch 1654/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0250 - accuracy: 1.0000 - val_loss: 1.0349 - val_accuracy: 0.7857\n",
            "Epoch 1655/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0250 - accuracy: 1.0000 - val_loss: 1.0355 - val_accuracy: 0.7857\n",
            "Epoch 1656/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0250 - accuracy: 1.0000 - val_loss: 1.0363 - val_accuracy: 0.7857\n",
            "Epoch 1657/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0249 - accuracy: 1.0000 - val_loss: 1.0372 - val_accuracy: 0.7857\n",
            "Epoch 1658/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0249 - accuracy: 1.0000 - val_loss: 1.0380 - val_accuracy: 0.7857\n",
            "Epoch 1659/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0248 - accuracy: 1.0000 - val_loss: 1.0386 - val_accuracy: 0.7857\n",
            "Epoch 1660/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0248 - accuracy: 1.0000 - val_loss: 1.0393 - val_accuracy: 0.7857\n",
            "Epoch 1661/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0248 - accuracy: 1.0000 - val_loss: 1.0398 - val_accuracy: 0.7857\n",
            "Epoch 1662/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0247 - accuracy: 1.0000 - val_loss: 1.0404 - val_accuracy: 0.7857\n",
            "Epoch 1663/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0247 - accuracy: 1.0000 - val_loss: 1.0409 - val_accuracy: 0.7857\n",
            "Epoch 1664/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0246 - accuracy: 1.0000 - val_loss: 1.0415 - val_accuracy: 0.7857\n",
            "Epoch 1665/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0246 - accuracy: 1.0000 - val_loss: 1.0422 - val_accuracy: 0.7857\n",
            "Epoch 1666/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0246 - accuracy: 1.0000 - val_loss: 1.0429 - val_accuracy: 0.7857\n",
            "Epoch 1667/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0245 - accuracy: 1.0000 - val_loss: 1.0436 - val_accuracy: 0.7857\n",
            "Epoch 1668/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0245 - accuracy: 1.0000 - val_loss: 1.0443 - val_accuracy: 0.7857\n",
            "Epoch 1669/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0244 - accuracy: 1.0000 - val_loss: 1.0450 - val_accuracy: 0.7857\n",
            "Epoch 1670/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0244 - accuracy: 1.0000 - val_loss: 1.0457 - val_accuracy: 0.7857\n",
            "Epoch 1671/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0244 - accuracy: 1.0000 - val_loss: 1.0464 - val_accuracy: 0.7857\n",
            "Epoch 1672/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0243 - accuracy: 1.0000 - val_loss: 1.0470 - val_accuracy: 0.7857\n",
            "Epoch 1673/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0243 - accuracy: 1.0000 - val_loss: 1.0476 - val_accuracy: 0.7857\n",
            "Epoch 1674/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0242 - accuracy: 1.0000 - val_loss: 1.0481 - val_accuracy: 0.7857\n",
            "Epoch 1675/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0242 - accuracy: 1.0000 - val_loss: 1.0488 - val_accuracy: 0.7857\n",
            "Epoch 1676/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0242 - accuracy: 1.0000 - val_loss: 1.0495 - val_accuracy: 0.7857\n",
            "Epoch 1677/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0241 - accuracy: 1.0000 - val_loss: 1.0501 - val_accuracy: 0.7857\n",
            "Epoch 1678/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0241 - accuracy: 1.0000 - val_loss: 1.0508 - val_accuracy: 0.7857\n",
            "Epoch 1679/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0240 - accuracy: 1.0000 - val_loss: 1.0514 - val_accuracy: 0.7857\n",
            "Epoch 1680/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0240 - accuracy: 1.0000 - val_loss: 1.0521 - val_accuracy: 0.7857\n",
            "Epoch 1681/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0240 - accuracy: 1.0000 - val_loss: 1.0527 - val_accuracy: 0.7857\n",
            "Epoch 1682/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0239 - accuracy: 1.0000 - val_loss: 1.0533 - val_accuracy: 0.7857\n",
            "Epoch 1683/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0239 - accuracy: 1.0000 - val_loss: 1.0538 - val_accuracy: 0.7857\n",
            "Epoch 1684/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0238 - accuracy: 1.0000 - val_loss: 1.0544 - val_accuracy: 0.7857\n",
            "Epoch 1685/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0238 - accuracy: 1.0000 - val_loss: 1.0550 - val_accuracy: 0.7857\n",
            "Epoch 1686/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0238 - accuracy: 1.0000 - val_loss: 1.0555 - val_accuracy: 0.7857\n",
            "Epoch 1687/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0237 - accuracy: 1.0000 - val_loss: 1.0561 - val_accuracy: 0.7857\n",
            "Epoch 1688/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0237 - accuracy: 1.0000 - val_loss: 1.0568 - val_accuracy: 0.7857\n",
            "Epoch 1689/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0237 - accuracy: 1.0000 - val_loss: 1.0575 - val_accuracy: 0.7857\n",
            "Epoch 1690/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0236 - accuracy: 1.0000 - val_loss: 1.0582 - val_accuracy: 0.7857\n",
            "Epoch 1691/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0236 - accuracy: 1.0000 - val_loss: 1.0588 - val_accuracy: 0.7857\n",
            "Epoch 1692/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 1.0595 - val_accuracy: 0.7857\n",
            "Epoch 1693/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 1.0602 - val_accuracy: 0.7857\n",
            "Epoch 1694/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 1.0609 - val_accuracy: 0.7857\n",
            "Epoch 1695/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 1.0614 - val_accuracy: 0.7857\n",
            "Epoch 1696/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 1.0620 - val_accuracy: 0.7857\n",
            "Epoch 1697/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 1.0626 - val_accuracy: 0.7857\n",
            "Epoch 1698/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 1.0633 - val_accuracy: 0.7857\n",
            "Epoch 1699/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 1.0642 - val_accuracy: 0.7857\n",
            "Epoch 1700/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 1.0648 - val_accuracy: 0.7857\n",
            "Epoch 1701/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 1.0654 - val_accuracy: 0.7857\n",
            "Epoch 1702/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 1.0660 - val_accuracy: 0.7857\n",
            "Epoch 1703/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0231 - accuracy: 1.0000 - val_loss: 1.0666 - val_accuracy: 0.7857\n",
            "Epoch 1704/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0231 - accuracy: 1.0000 - val_loss: 1.0672 - val_accuracy: 0.7857\n",
            "Epoch 1705/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 1.0678 - val_accuracy: 0.7857\n",
            "Epoch 1706/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 1.0684 - val_accuracy: 0.7857\n",
            "Epoch 1707/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 1.0690 - val_accuracy: 0.7857\n",
            "Epoch 1708/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 1.0697 - val_accuracy: 0.7857\n",
            "Epoch 1709/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 1.0703 - val_accuracy: 0.7857\n",
            "Epoch 1710/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 1.0710 - val_accuracy: 0.7857\n",
            "Epoch 1711/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 1.0716 - val_accuracy: 0.7857\n",
            "Epoch 1712/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 1.0724 - val_accuracy: 0.7857\n",
            "Epoch 1713/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 1.0730 - val_accuracy: 0.7857\n",
            "Epoch 1714/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 1.0735 - val_accuracy: 0.7857\n",
            "Epoch 1715/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 1.0740 - val_accuracy: 0.7857\n",
            "Epoch 1716/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 1.0745 - val_accuracy: 0.7857\n",
            "Epoch 1717/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 1.0750 - val_accuracy: 0.7857\n",
            "Epoch 1718/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 1.0756 - val_accuracy: 0.7857\n",
            "Epoch 1719/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 1.0764 - val_accuracy: 0.7857\n",
            "Epoch 1720/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 1.0771 - val_accuracy: 0.7857\n",
            "Epoch 1721/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 1.0777 - val_accuracy: 0.7857\n",
            "Epoch 1722/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 1.0784 - val_accuracy: 0.7857\n",
            "Epoch 1723/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 1.0790 - val_accuracy: 0.7857\n",
            "Epoch 1724/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 1.0796 - val_accuracy: 0.7857\n",
            "Epoch 1725/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 1.0802 - val_accuracy: 0.7857\n",
            "Epoch 1726/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 1.0807 - val_accuracy: 0.7857\n",
            "Epoch 1727/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 1.0812 - val_accuracy: 0.7857\n",
            "Epoch 1728/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 1.0818 - val_accuracy: 0.7857\n",
            "Epoch 1729/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 1.0825 - val_accuracy: 0.7857\n",
            "Epoch 1730/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 1.0831 - val_accuracy: 0.7857\n",
            "Epoch 1731/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 1.0838 - val_accuracy: 0.7857\n",
            "Epoch 1732/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 1.0844 - val_accuracy: 0.7857\n",
            "Epoch 1733/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 1.0850 - val_accuracy: 0.7857\n",
            "Epoch 1734/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 1.0856 - val_accuracy: 0.7857\n",
            "Epoch 1735/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 1.0862 - val_accuracy: 0.7857\n",
            "Epoch 1736/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 1.0868 - val_accuracy: 0.7857\n",
            "Epoch 1737/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 1.0874 - val_accuracy: 0.7857\n",
            "Epoch 1738/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 1.0881 - val_accuracy: 0.7857\n",
            "Epoch 1739/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 1.0888 - val_accuracy: 0.7857\n",
            "Epoch 1740/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 1.0895 - val_accuracy: 0.7857\n",
            "Epoch 1741/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 1.0901 - val_accuracy: 0.7857\n",
            "Epoch 1742/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 1.0907 - val_accuracy: 0.7857\n",
            "Epoch 1743/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 1.0913 - val_accuracy: 0.7857\n",
            "Epoch 1744/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 1.0918 - val_accuracy: 0.7857\n",
            "Epoch 1745/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 1.0923 - val_accuracy: 0.7857\n",
            "Epoch 1746/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 1.0928 - val_accuracy: 0.7857\n",
            "Epoch 1747/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 1.0934 - val_accuracy: 0.7857\n",
            "Epoch 1748/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 1.0941 - val_accuracy: 0.7857\n",
            "Epoch 1749/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 1.0948 - val_accuracy: 0.7857\n",
            "Epoch 1750/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 1.0955 - val_accuracy: 0.7857\n",
            "Epoch 1751/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 1.0962 - val_accuracy: 0.7857\n",
            "Epoch 1752/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 1.0969 - val_accuracy: 0.7857\n",
            "Epoch 1753/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 1.0975 - val_accuracy: 0.7857\n",
            "Epoch 1754/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 1.0981 - val_accuracy: 0.7857\n",
            "Epoch 1755/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 1.0985 - val_accuracy: 0.7857\n",
            "Epoch 1756/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 1.0989 - val_accuracy: 0.7857\n",
            "Epoch 1757/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 1.0995 - val_accuracy: 0.7857\n",
            "Epoch 1758/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 1.1000 - val_accuracy: 0.7857\n",
            "Epoch 1759/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 1.1006 - val_accuracy: 0.7857\n",
            "Epoch 1760/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 1.1013 - val_accuracy: 0.7857\n",
            "Epoch 1761/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 1.1020 - val_accuracy: 0.7857\n",
            "Epoch 1762/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 1.1028 - val_accuracy: 0.7857\n",
            "Epoch 1763/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 1.1034 - val_accuracy: 0.7857\n",
            "Epoch 1764/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 1.1040 - val_accuracy: 0.7857\n",
            "Epoch 1765/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 1.1045 - val_accuracy: 0.7857\n",
            "Epoch 1766/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 1.1049 - val_accuracy: 0.7857\n",
            "Epoch 1767/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 1.1054 - val_accuracy: 0.7857\n",
            "Epoch 1768/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 1.1060 - val_accuracy: 0.7857\n",
            "Epoch 1769/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 1.1065 - val_accuracy: 0.7857\n",
            "Epoch 1770/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 1.1070 - val_accuracy: 0.7857\n",
            "Epoch 1771/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 1.1077 - val_accuracy: 0.7857\n",
            "Epoch 1772/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 1.1085 - val_accuracy: 0.7857\n",
            "Epoch 1773/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 1.1093 - val_accuracy: 0.7857\n",
            "Epoch 1774/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 1.1100 - val_accuracy: 0.7857\n",
            "Epoch 1775/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 1.1105 - val_accuracy: 0.7857\n",
            "Epoch 1776/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 1.1109 - val_accuracy: 0.7857\n",
            "Epoch 1777/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 1.1114 - val_accuracy: 0.7857\n",
            "Epoch 1778/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 1.1119 - val_accuracy: 0.7857\n",
            "Epoch 1779/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 1.1125 - val_accuracy: 0.7857\n",
            "Epoch 1780/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 1.1131 - val_accuracy: 0.7857\n",
            "Epoch 1781/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 1.1137 - val_accuracy: 0.7857\n",
            "Epoch 1782/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 1.1145 - val_accuracy: 0.7857\n",
            "Epoch 1783/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 1.1152 - val_accuracy: 0.7857\n",
            "Epoch 1784/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 1.1158 - val_accuracy: 0.7857\n",
            "Epoch 1785/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 1.1163 - val_accuracy: 0.7857\n",
            "Epoch 1786/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 1.1169 - val_accuracy: 0.7857\n",
            "Epoch 1787/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 1.1174 - val_accuracy: 0.7857\n",
            "Epoch 1788/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 1.1179 - val_accuracy: 0.7857\n",
            "Epoch 1789/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 1.1183 - val_accuracy: 0.7857\n",
            "Epoch 1790/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 1.1188 - val_accuracy: 0.7857\n",
            "Epoch 1791/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 1.1195 - val_accuracy: 0.7857\n",
            "Epoch 1792/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 1.1201 - val_accuracy: 0.7857\n",
            "Epoch 1793/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 1.1208 - val_accuracy: 0.7857\n",
            "Epoch 1794/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 1.1216 - val_accuracy: 0.7857\n",
            "Epoch 1795/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 1.1222 - val_accuracy: 0.7857\n",
            "Epoch 1796/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 1.1228 - val_accuracy: 0.7857\n",
            "Epoch 1797/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 1.1233 - val_accuracy: 0.7857\n",
            "Epoch 1798/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 1.1239 - val_accuracy: 0.7857\n",
            "Epoch 1799/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 1.1243 - val_accuracy: 0.7857\n",
            "Epoch 1800/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 1.1247 - val_accuracy: 0.7857\n",
            "Epoch 1801/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 1.1253 - val_accuracy: 0.7857\n",
            "Epoch 1802/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 1.1259 - val_accuracy: 0.7857\n",
            "Epoch 1803/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 1.1266 - val_accuracy: 0.7857\n",
            "Epoch 1804/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 1.1272 - val_accuracy: 0.7857\n",
            "Epoch 1805/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 1.1280 - val_accuracy: 0.7857\n",
            "Epoch 1806/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 1.1286 - val_accuracy: 0.7857\n",
            "Epoch 1807/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 1.1291 - val_accuracy: 0.7857\n",
            "Epoch 1808/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 1.1295 - val_accuracy: 0.7857\n",
            "Epoch 1809/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 1.1299 - val_accuracy: 0.7857\n",
            "Epoch 1810/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 1.1304 - val_accuracy: 0.7857\n",
            "Epoch 1811/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 1.1309 - val_accuracy: 0.7857\n",
            "Epoch 1812/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 1.1314 - val_accuracy: 0.7857\n",
            "Epoch 1813/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 1.1321 - val_accuracy: 0.7857\n",
            "Epoch 1814/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 1.1329 - val_accuracy: 0.7857\n",
            "Epoch 1815/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 1.1336 - val_accuracy: 0.7857\n",
            "Epoch 1816/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 1.1343 - val_accuracy: 0.7857\n",
            "Epoch 1817/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 1.1349 - val_accuracy: 0.7857\n",
            "Epoch 1818/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 1.1355 - val_accuracy: 0.7857\n",
            "Epoch 1819/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 1.1358 - val_accuracy: 0.7857\n",
            "Epoch 1820/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 1.1361 - val_accuracy: 0.7857\n",
            "Epoch 1821/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 1.1366 - val_accuracy: 0.7857\n",
            "Epoch 1822/4000\n",
            "1/1 [==============================] - 0s 109ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 1.1371 - val_accuracy: 0.7857\n",
            "Epoch 1823/4000\n",
            "1/1 [==============================] - 0s 154ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 1.1377 - val_accuracy: 0.7857\n",
            "Epoch 1824/4000\n",
            "1/1 [==============================] - 0s 168ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 1.1383 - val_accuracy: 0.7857\n",
            "Epoch 1825/4000\n",
            "1/1 [==============================] - 0s 244ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 1.1391 - val_accuracy: 0.7857\n",
            "Epoch 1826/4000\n",
            "1/1 [==============================] - 0s 158ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 1.1399 - val_accuracy: 0.7857\n",
            "Epoch 1827/4000\n",
            "1/1 [==============================] - 0s 95ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 1.1405 - val_accuracy: 0.7857\n",
            "Epoch 1828/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 1.1410 - val_accuracy: 0.7857\n",
            "Epoch 1829/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 1.1415 - val_accuracy: 0.7857\n",
            "Epoch 1830/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 1.1420 - val_accuracy: 0.7857\n",
            "Epoch 1831/4000\n",
            "1/1 [==============================] - 0s 37ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 1.1425 - val_accuracy: 0.7857\n",
            "Epoch 1832/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 1.1430 - val_accuracy: 0.7857\n",
            "Epoch 1833/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 1.1435 - val_accuracy: 0.7857\n",
            "Epoch 1834/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 1.1439 - val_accuracy: 0.7857\n",
            "Epoch 1835/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 1.1446 - val_accuracy: 0.7857\n",
            "Epoch 1836/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 1.1454 - val_accuracy: 0.7857\n",
            "Epoch 1837/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 1.1461 - val_accuracy: 0.7857\n",
            "Epoch 1838/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 1.1466 - val_accuracy: 0.7857\n",
            "Epoch 1839/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 1.1471 - val_accuracy: 0.7857\n",
            "Epoch 1840/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 1.1476 - val_accuracy: 0.7857\n",
            "Epoch 1841/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 1.1481 - val_accuracy: 0.7857\n",
            "Epoch 1842/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 1.1486 - val_accuracy: 0.7857\n",
            "Epoch 1843/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 1.1491 - val_accuracy: 0.7857\n",
            "Epoch 1844/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 1.1497 - val_accuracy: 0.7857\n",
            "Epoch 1845/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 1.1505 - val_accuracy: 0.7857\n",
            "Epoch 1846/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 1.1512 - val_accuracy: 0.7857\n",
            "Epoch 1847/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 1.1519 - val_accuracy: 0.7857\n",
            "Epoch 1848/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 1.1524 - val_accuracy: 0.7857\n",
            "Epoch 1849/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 1.1528 - val_accuracy: 0.7857\n",
            "Epoch 1850/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 1.1532 - val_accuracy: 0.7857\n",
            "Epoch 1851/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 1.1537 - val_accuracy: 0.7857\n",
            "Epoch 1852/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 1.1540 - val_accuracy: 0.7857\n",
            "Epoch 1853/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 1.1545 - val_accuracy: 0.7857\n",
            "Epoch 1854/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 1.1550 - val_accuracy: 0.7857\n",
            "Epoch 1855/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 1.1557 - val_accuracy: 0.7857\n",
            "Epoch 1856/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 1.1565 - val_accuracy: 0.7857\n",
            "Epoch 1857/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 1.1572 - val_accuracy: 0.7857\n",
            "Epoch 1858/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 1.1578 - val_accuracy: 0.7857\n",
            "Epoch 1859/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 1.1583 - val_accuracy: 0.7857\n",
            "Epoch 1860/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 1.1589 - val_accuracy: 0.7857\n",
            "Epoch 1861/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 1.1593 - val_accuracy: 0.7857\n",
            "Epoch 1862/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 1.1597 - val_accuracy: 0.7857\n",
            "Epoch 1863/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 1.1601 - val_accuracy: 0.7857\n",
            "Epoch 1864/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 1.1606 - val_accuracy: 0.7857\n",
            "Epoch 1865/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 1.1611 - val_accuracy: 0.7857\n",
            "Epoch 1866/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 1.1619 - val_accuracy: 0.7857\n",
            "Epoch 1867/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 1.1626 - val_accuracy: 0.7857\n",
            "Epoch 1868/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 1.1632 - val_accuracy: 0.7857\n",
            "Epoch 1869/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 1.1638 - val_accuracy: 0.7857\n",
            "Epoch 1870/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 1.1645 - val_accuracy: 0.7857\n",
            "Epoch 1871/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 1.1650 - val_accuracy: 0.7857\n",
            "Epoch 1872/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 1.1654 - val_accuracy: 0.7857\n",
            "Epoch 1873/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 1.1657 - val_accuracy: 0.7857\n",
            "Epoch 1874/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 1.1662 - val_accuracy: 0.7857\n",
            "Epoch 1875/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 1.1668 - val_accuracy: 0.7857\n",
            "Epoch 1876/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 1.1674 - val_accuracy: 0.7857\n",
            "Epoch 1877/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 1.1680 - val_accuracy: 0.7714\n",
            "Epoch 1878/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 1.1687 - val_accuracy: 0.7714\n",
            "Epoch 1879/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 1.1694 - val_accuracy: 0.7714\n",
            "Epoch 1880/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 1.1699 - val_accuracy: 0.7714\n",
            "Epoch 1881/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 1.1705 - val_accuracy: 0.7714\n",
            "Epoch 1882/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 1.1710 - val_accuracy: 0.7714\n",
            "Epoch 1883/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 1.1714 - val_accuracy: 0.7714\n",
            "Epoch 1884/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 1.1718 - val_accuracy: 0.7714\n",
            "Epoch 1885/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 1.1722 - val_accuracy: 0.7714\n",
            "Epoch 1886/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 1.1728 - val_accuracy: 0.7714\n",
            "Epoch 1887/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 1.1734 - val_accuracy: 0.7714\n",
            "Epoch 1888/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 1.1740 - val_accuracy: 0.7714\n",
            "Epoch 1889/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 1.1747 - val_accuracy: 0.7714\n",
            "Epoch 1890/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 1.1753 - val_accuracy: 0.7714\n",
            "Epoch 1891/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 1.1759 - val_accuracy: 0.7714\n",
            "Epoch 1892/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 1.1765 - val_accuracy: 0.7714\n",
            "Epoch 1893/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 1.1768 - val_accuracy: 0.7714\n",
            "Epoch 1894/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 1.1771 - val_accuracy: 0.7714\n",
            "Epoch 1895/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 1.1775 - val_accuracy: 0.7714\n",
            "Epoch 1896/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 1.1780 - val_accuracy: 0.7714\n",
            "Epoch 1897/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 1.1787 - val_accuracy: 0.7714\n",
            "Epoch 1898/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 1.1794 - val_accuracy: 0.7714\n",
            "Epoch 1899/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 1.1800 - val_accuracy: 0.7714\n",
            "Epoch 1900/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 1.1806 - val_accuracy: 0.7714\n",
            "Epoch 1901/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 1.1811 - val_accuracy: 0.7714\n",
            "Epoch 1902/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 1.1817 - val_accuracy: 0.7714\n",
            "Epoch 1903/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 1.1821 - val_accuracy: 0.7714\n",
            "Epoch 1904/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 1.1825 - val_accuracy: 0.7714\n",
            "Epoch 1905/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 1.1831 - val_accuracy: 0.7714\n",
            "Epoch 1906/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 1.1836 - val_accuracy: 0.7714\n",
            "Epoch 1907/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 1.1842 - val_accuracy: 0.7714\n",
            "Epoch 1908/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 1.1848 - val_accuracy: 0.7714\n",
            "Epoch 1909/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 1.1854 - val_accuracy: 0.7714\n",
            "Epoch 1910/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 1.1861 - val_accuracy: 0.7714\n",
            "Epoch 1911/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 1.1868 - val_accuracy: 0.7714\n",
            "Epoch 1912/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 1.1874 - val_accuracy: 0.7714\n",
            "Epoch 1913/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 1.1879 - val_accuracy: 0.7714\n",
            "Epoch 1914/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 1.1882 - val_accuracy: 0.7714\n",
            "Epoch 1915/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 1.1886 - val_accuracy: 0.7714\n",
            "Epoch 1916/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 1.1891 - val_accuracy: 0.7714\n",
            "Epoch 1917/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 1.1896 - val_accuracy: 0.7714\n",
            "Epoch 1918/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 1.1901 - val_accuracy: 0.7714\n",
            "Epoch 1919/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 1.1907 - val_accuracy: 0.7714\n",
            "Epoch 1920/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 1.1914 - val_accuracy: 0.7714\n",
            "Epoch 1921/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 1.1919 - val_accuracy: 0.7714\n",
            "Epoch 1922/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 1.1924 - val_accuracy: 0.7714\n",
            "Epoch 1923/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 1.1930 - val_accuracy: 0.7714\n",
            "Epoch 1924/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 1.1935 - val_accuracy: 0.7714\n",
            "Epoch 1925/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 1.1940 - val_accuracy: 0.7714\n",
            "Epoch 1926/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 1.1944 - val_accuracy: 0.7714\n",
            "Epoch 1927/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 1.1949 - val_accuracy: 0.7714\n",
            "Epoch 1928/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 1.1955 - val_accuracy: 0.7714\n",
            "Epoch 1929/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 1.1962 - val_accuracy: 0.7714\n",
            "Epoch 1930/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 1.1968 - val_accuracy: 0.7714\n",
            "Epoch 1931/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 1.1975 - val_accuracy: 0.7714\n",
            "Epoch 1932/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 1.1980 - val_accuracy: 0.7714\n",
            "Epoch 1933/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 1.1984 - val_accuracy: 0.7714\n",
            "Epoch 1934/4000\n",
            "1/1 [==============================] - 0s 37ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 1.1988 - val_accuracy: 0.7714\n",
            "Epoch 1935/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 1.1992 - val_accuracy: 0.7714\n",
            "Epoch 1936/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 1.1995 - val_accuracy: 0.7714\n",
            "Epoch 1937/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 1.1999 - val_accuracy: 0.7714\n",
            "Epoch 1938/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 1.2004 - val_accuracy: 0.7714\n",
            "Epoch 1939/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 1.2011 - val_accuracy: 0.7714\n",
            "Epoch 1940/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 1.2018 - val_accuracy: 0.7714\n",
            "Epoch 1941/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 1.2024 - val_accuracy: 0.7714\n",
            "Epoch 1942/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 1.2031 - val_accuracy: 0.7714\n",
            "Epoch 1943/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 1.2038 - val_accuracy: 0.7714\n",
            "Epoch 1944/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 1.2043 - val_accuracy: 0.7714\n",
            "Epoch 1945/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 1.2047 - val_accuracy: 0.7714\n",
            "Epoch 1946/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 1.2050 - val_accuracy: 0.7714\n",
            "Epoch 1947/4000\n",
            "1/1 [==============================] - 0s 94ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 1.2054 - val_accuracy: 0.7714\n",
            "Epoch 1948/4000\n",
            "1/1 [==============================] - 0s 255ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 1.2057 - val_accuracy: 0.7714\n",
            "Epoch 1949/4000\n",
            "1/1 [==============================] - 0s 101ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 1.2062 - val_accuracy: 0.7714\n",
            "Epoch 1950/4000\n",
            "1/1 [==============================] - 0s 179ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 1.2069 - val_accuracy: 0.7714\n",
            "Epoch 1951/4000\n",
            "1/1 [==============================] - 0s 131ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 1.2076 - val_accuracy: 0.7714\n",
            "Epoch 1952/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 1.2083 - val_accuracy: 0.7714\n",
            "Epoch 1953/4000\n",
            "1/1 [==============================] - 0s 176ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 1.2089 - val_accuracy: 0.7714\n",
            "Epoch 1954/4000\n",
            "1/1 [==============================] - 0s 197ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 1.2095 - val_accuracy: 0.7714\n",
            "Epoch 1955/4000\n",
            "1/1 [==============================] - 0s 162ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 1.2099 - val_accuracy: 0.7714\n",
            "Epoch 1956/4000\n",
            "1/1 [==============================] - 0s 124ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 1.2102 - val_accuracy: 0.7714\n",
            "Epoch 1957/4000\n",
            "1/1 [==============================] - 0s 94ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 1.2106 - val_accuracy: 0.7714\n",
            "Epoch 1958/4000\n",
            "1/1 [==============================] - 0s 154ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 1.2110 - val_accuracy: 0.7714\n",
            "Epoch 1959/4000\n",
            "1/1 [==============================] - 0s 108ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 1.2115 - val_accuracy: 0.7714\n",
            "Epoch 1960/4000\n",
            "1/1 [==============================] - 0s 115ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 1.2122 - val_accuracy: 0.7714\n",
            "Epoch 1961/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 1.2129 - val_accuracy: 0.7714\n",
            "Epoch 1962/4000\n",
            "1/1 [==============================] - 0s 139ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 1.2135 - val_accuracy: 0.7714\n",
            "Epoch 1963/4000\n",
            "1/1 [==============================] - 0s 121ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 1.2142 - val_accuracy: 0.7714\n",
            "Epoch 1964/4000\n",
            "1/1 [==============================] - 0s 84ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 1.2148 - val_accuracy: 0.7714\n",
            "Epoch 1965/4000\n",
            "1/1 [==============================] - 0s 128ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 1.2153 - val_accuracy: 0.7714\n",
            "Epoch 1966/4000\n",
            "1/1 [==============================] - 0s 95ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 1.2157 - val_accuracy: 0.7714\n",
            "Epoch 1967/4000\n",
            "1/1 [==============================] - 0s 116ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 1.2160 - val_accuracy: 0.7714\n",
            "Epoch 1968/4000\n",
            "1/1 [==============================] - 0s 134ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 1.2164 - val_accuracy: 0.7714\n",
            "Epoch 1969/4000\n",
            "1/1 [==============================] - 0s 97ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 1.2168 - val_accuracy: 0.7714\n",
            "Epoch 1970/4000\n",
            "1/1 [==============================] - 0s 129ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 1.2173 - val_accuracy: 0.7714\n",
            "Epoch 1971/4000\n",
            "1/1 [==============================] - 0s 171ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 1.2180 - val_accuracy: 0.7714\n",
            "Epoch 1972/4000\n",
            "1/1 [==============================] - 0s 112ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 1.2187 - val_accuracy: 0.7714\n",
            "Epoch 1973/4000\n",
            "1/1 [==============================] - 0s 97ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 1.2194 - val_accuracy: 0.7714\n",
            "Epoch 1974/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 1.2200 - val_accuracy: 0.7714\n",
            "Epoch 1975/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 1.2205 - val_accuracy: 0.7714\n",
            "Epoch 1976/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 1.2207 - val_accuracy: 0.7714\n",
            "Epoch 1977/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 1.2210 - val_accuracy: 0.7714\n",
            "Epoch 1978/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 1.2213 - val_accuracy: 0.7714\n",
            "Epoch 1979/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 1.2218 - val_accuracy: 0.7714\n",
            "Epoch 1980/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 1.2224 - val_accuracy: 0.7714\n",
            "Epoch 1981/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 1.2230 - val_accuracy: 0.7714\n",
            "Epoch 1982/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 1.2238 - val_accuracy: 0.7714\n",
            "Epoch 1983/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 1.2246 - val_accuracy: 0.7714\n",
            "Epoch 1984/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 1.2252 - val_accuracy: 0.7714\n",
            "Epoch 1985/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 1.2257 - val_accuracy: 0.7714\n",
            "Epoch 1986/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 1.2261 - val_accuracy: 0.7714\n",
            "Epoch 1987/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 1.2264 - val_accuracy: 0.7714\n",
            "Epoch 1988/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 1.2268 - val_accuracy: 0.7714\n",
            "Epoch 1989/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 1.2271 - val_accuracy: 0.7714\n",
            "Epoch 1990/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 1.2274 - val_accuracy: 0.7714\n",
            "Epoch 1991/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 1.2279 - val_accuracy: 0.7714\n",
            "Epoch 1992/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 1.2286 - val_accuracy: 0.7714\n",
            "Epoch 1993/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 1.2294 - val_accuracy: 0.7714\n",
            "Epoch 1994/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 1.2302 - val_accuracy: 0.7714\n",
            "Epoch 1995/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 1.2309 - val_accuracy: 0.7714\n",
            "Epoch 1996/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 1.2313 - val_accuracy: 0.7714\n",
            "Epoch 1997/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 1.2317 - val_accuracy: 0.7714\n",
            "Epoch 1998/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 1.2321 - val_accuracy: 0.7714\n",
            "Epoch 1999/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 1.2325 - val_accuracy: 0.7714\n",
            "Epoch 2000/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 1.2329 - val_accuracy: 0.7714\n",
            "Epoch 2001/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 1.2333 - val_accuracy: 0.7714\n",
            "Epoch 2002/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 1.2339 - val_accuracy: 0.7714\n",
            "Epoch 2003/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 1.2346 - val_accuracy: 0.7714\n",
            "Epoch 2004/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 1.2353 - val_accuracy: 0.7714\n",
            "Epoch 2005/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 1.2358 - val_accuracy: 0.7714\n",
            "Epoch 2006/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 1.2363 - val_accuracy: 0.7714\n",
            "Epoch 2007/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 1.2367 - val_accuracy: 0.7714\n",
            "Epoch 2008/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 1.2371 - val_accuracy: 0.7714\n",
            "Epoch 2009/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 1.2376 - val_accuracy: 0.7714\n",
            "Epoch 2010/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 1.2379 - val_accuracy: 0.7714\n",
            "Epoch 2011/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 1.2382 - val_accuracy: 0.7714\n",
            "Epoch 2012/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 1.2387 - val_accuracy: 0.7714\n",
            "Epoch 2013/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 1.2395 - val_accuracy: 0.7714\n",
            "Epoch 2014/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 1.2404 - val_accuracy: 0.7714\n",
            "Epoch 2015/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 1.2412 - val_accuracy: 0.7714\n",
            "Epoch 2016/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 1.2416 - val_accuracy: 0.7714\n",
            "Epoch 2017/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 1.2421 - val_accuracy: 0.7714\n",
            "Epoch 2018/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 1.2425 - val_accuracy: 0.7714\n",
            "Epoch 2019/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 1.2427 - val_accuracy: 0.7714\n",
            "Epoch 2020/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 1.2430 - val_accuracy: 0.7714\n",
            "Epoch 2021/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 1.2433 - val_accuracy: 0.7714\n",
            "Epoch 2022/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 1.2437 - val_accuracy: 0.7714\n",
            "Epoch 2023/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 1.2443 - val_accuracy: 0.7714\n",
            "Epoch 2024/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 1.2450 - val_accuracy: 0.7714\n",
            "Epoch 2025/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 1.2457 - val_accuracy: 0.7714\n",
            "Epoch 2026/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 1.2464 - val_accuracy: 0.7714\n",
            "Epoch 2027/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 1.2469 - val_accuracy: 0.7714\n",
            "Epoch 2028/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2474 - val_accuracy: 0.7714\n",
            "Epoch 2029/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2480 - val_accuracy: 0.7714\n",
            "Epoch 2030/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2483 - val_accuracy: 0.7714\n",
            "Epoch 2031/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2486 - val_accuracy: 0.7714\n",
            "Epoch 2032/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2489 - val_accuracy: 0.7714\n",
            "Epoch 2033/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 1.2494 - val_accuracy: 0.7714\n",
            "Epoch 2034/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 1.2501 - val_accuracy: 0.7714\n",
            "Epoch 2035/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 1.2507 - val_accuracy: 0.7714\n",
            "Epoch 2036/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 1.2514 - val_accuracy: 0.7714\n",
            "Epoch 2037/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 1.2520 - val_accuracy: 0.7714\n",
            "Epoch 2038/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 1.2526 - val_accuracy: 0.7714\n",
            "Epoch 2039/4000\n",
            "1/1 [==============================] - 0s 113ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 1.2531 - val_accuracy: 0.7714\n",
            "Epoch 2040/4000\n",
            "1/1 [==============================] - 0s 176ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 1.2533 - val_accuracy: 0.7714\n",
            "Epoch 2041/4000\n",
            "1/1 [==============================] - 0s 148ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 1.2536 - val_accuracy: 0.7714\n",
            "Epoch 2042/4000\n",
            "1/1 [==============================] - 0s 145ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 1.2539 - val_accuracy: 0.7714\n",
            "Epoch 2043/4000\n",
            "1/1 [==============================] - 0s 89ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.2544 - val_accuracy: 0.7714\n",
            "Epoch 2044/4000\n",
            "1/1 [==============================] - 0s 176ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.2550 - val_accuracy: 0.7714\n",
            "Epoch 2045/4000\n",
            "1/1 [==============================] - 0s 108ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.2556 - val_accuracy: 0.7714\n",
            "Epoch 2046/4000\n",
            "1/1 [==============================] - 0s 96ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.2564 - val_accuracy: 0.7714\n",
            "Epoch 2047/4000\n",
            "1/1 [==============================] - 0s 94ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 1.2571 - val_accuracy: 0.7714\n",
            "Epoch 2048/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 1.2577 - val_accuracy: 0.7714\n",
            "Epoch 2049/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 1.2583 - val_accuracy: 0.7714\n",
            "Epoch 2050/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 1.2587 - val_accuracy: 0.7714\n",
            "Epoch 2051/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 1.2590 - val_accuracy: 0.7714\n",
            "Epoch 2052/4000\n",
            "1/1 [==============================] - 0s 110ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 1.2592 - val_accuracy: 0.7714\n",
            "Epoch 2053/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2595 - val_accuracy: 0.7714\n",
            "Epoch 2054/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2600 - val_accuracy: 0.7714\n",
            "Epoch 2055/4000\n",
            "1/1 [==============================] - 0s 95ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2605 - val_accuracy: 0.7714\n",
            "Epoch 2056/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2612 - val_accuracy: 0.7714\n",
            "Epoch 2057/4000\n",
            "1/1 [==============================] - 0s 95ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2619 - val_accuracy: 0.7714\n",
            "Epoch 2058/4000\n",
            "1/1 [==============================] - 0s 128ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 1.2625 - val_accuracy: 0.7714\n",
            "Epoch 2059/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 1.2632 - val_accuracy: 0.7714\n",
            "Epoch 2060/4000\n",
            "1/1 [==============================] - 0s 158ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 1.2636 - val_accuracy: 0.7714\n",
            "Epoch 2061/4000\n",
            "1/1 [==============================] - 0s 90ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 1.2640 - val_accuracy: 0.7714\n",
            "Epoch 2062/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 1.2643 - val_accuracy: 0.7714\n",
            "Epoch 2063/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 1.2647 - val_accuracy: 0.7714\n",
            "Epoch 2064/4000\n",
            "1/1 [==============================] - 0s 138ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 1.2649 - val_accuracy: 0.7714\n",
            "Epoch 2065/4000\n",
            "1/1 [==============================] - 0s 104ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 1.2653 - val_accuracy: 0.7714\n",
            "Epoch 2066/4000\n",
            "1/1 [==============================] - 0s 93ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 1.2659 - val_accuracy: 0.7714\n",
            "Epoch 2067/4000\n",
            "1/1 [==============================] - 0s 84ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 1.2666 - val_accuracy: 0.7714\n",
            "Epoch 2068/4000\n",
            "1/1 [==============================] - 0s 169ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 1.2674 - val_accuracy: 0.7714\n",
            "Epoch 2069/4000\n",
            "1/1 [==============================] - 0s 110ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.2680 - val_accuracy: 0.7714\n",
            "Epoch 2070/4000\n",
            "1/1 [==============================] - 0s 96ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.2685 - val_accuracy: 0.7714\n",
            "Epoch 2071/4000\n",
            "1/1 [==============================] - 0s 103ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.2690 - val_accuracy: 0.7714\n",
            "Epoch 2072/4000\n",
            "1/1 [==============================] - 0s 194ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.2695 - val_accuracy: 0.7714\n",
            "Epoch 2073/4000\n",
            "1/1 [==============================] - 0s 230ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 1.2698 - val_accuracy: 0.7714\n",
            "Epoch 2074/4000\n",
            "1/1 [==============================] - 0s 267ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2700 - val_accuracy: 0.7714\n",
            "Epoch 2075/4000\n",
            "1/1 [==============================] - 0s 157ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2703 - val_accuracy: 0.7714\n",
            "Epoch 2076/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2707 - val_accuracy: 0.7714\n",
            "Epoch 2077/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2713 - val_accuracy: 0.7714\n",
            "Epoch 2078/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2719 - val_accuracy: 0.7714\n",
            "Epoch 2079/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 1.2726 - val_accuracy: 0.7714\n",
            "Epoch 2080/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 1.2732 - val_accuracy: 0.7714\n",
            "Epoch 2081/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 1.2737 - val_accuracy: 0.7714\n",
            "Epoch 2082/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 1.2742 - val_accuracy: 0.7714\n",
            "Epoch 2083/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 1.2747 - val_accuracy: 0.7714\n",
            "Epoch 2084/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 1.2751 - val_accuracy: 0.7714\n",
            "Epoch 2085/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2754 - val_accuracy: 0.7714\n",
            "Epoch 2086/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2757 - val_accuracy: 0.7714\n",
            "Epoch 2087/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2763 - val_accuracy: 0.7714\n",
            "Epoch 2088/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2769 - val_accuracy: 0.7714\n",
            "Epoch 2089/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2776 - val_accuracy: 0.7714\n",
            "Epoch 2090/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 1.2783 - val_accuracy: 0.7714\n",
            "Epoch 2091/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 1.2788 - val_accuracy: 0.7714\n",
            "Epoch 2092/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 1.2792 - val_accuracy: 0.7714\n",
            "Epoch 2093/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 1.2796 - val_accuracy: 0.7714\n",
            "Epoch 2094/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 1.2799 - val_accuracy: 0.7714\n",
            "Epoch 2095/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 1.2802 - val_accuracy: 0.7714\n",
            "Epoch 2096/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2806 - val_accuracy: 0.7714\n",
            "Epoch 2097/4000\n",
            "1/1 [==============================] - 0s 229ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2811 - val_accuracy: 0.7714\n",
            "Epoch 2098/4000\n",
            "1/1 [==============================] - 0s 114ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2817 - val_accuracy: 0.7714\n",
            "Epoch 2099/4000\n",
            "1/1 [==============================] - 0s 204ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2824 - val_accuracy: 0.7714\n",
            "Epoch 2100/4000\n",
            "1/1 [==============================] - 0s 132ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2831 - val_accuracy: 0.7714\n",
            "Epoch 2101/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 1.2836 - val_accuracy: 0.7714\n",
            "Epoch 2102/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 1.2842 - val_accuracy: 0.7571\n",
            "Epoch 2103/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 1.2846 - val_accuracy: 0.7714\n",
            "Epoch 2104/4000\n",
            "1/1 [==============================] - 0s 165ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 1.2849 - val_accuracy: 0.7714\n",
            "Epoch 2105/4000\n",
            "1/1 [==============================] - 0s 96ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 1.2853 - val_accuracy: 0.7714\n",
            "Epoch 2106/4000\n",
            "1/1 [==============================] - 0s 108ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 1.2856 - val_accuracy: 0.7714\n",
            "Epoch 2107/4000\n",
            "1/1 [==============================] - 0s 161ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2860 - val_accuracy: 0.7714\n",
            "Epoch 2108/4000\n",
            "1/1 [==============================] - 0s 87ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2865 - val_accuracy: 0.7714\n",
            "Epoch 2109/4000\n",
            "1/1 [==============================] - 0s 161ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2871 - val_accuracy: 0.7714\n",
            "Epoch 2110/4000\n",
            "1/1 [==============================] - 0s 130ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2878 - val_accuracy: 0.7714\n",
            "Epoch 2111/4000\n",
            "1/1 [==============================] - 0s 87ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2884 - val_accuracy: 0.7714\n",
            "Epoch 2112/4000\n",
            "1/1 [==============================] - 0s 114ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 1.2888 - val_accuracy: 0.7714\n",
            "Epoch 2113/4000\n",
            "1/1 [==============================] - 0s 153ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2892 - val_accuracy: 0.7714\n",
            "Epoch 2114/4000\n",
            "1/1 [==============================] - 0s 121ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2895 - val_accuracy: 0.7714\n",
            "Epoch 2115/4000\n",
            "1/1 [==============================] - 0s 104ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2898 - val_accuracy: 0.7714\n",
            "Epoch 2116/4000\n",
            "1/1 [==============================] - 0s 107ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2902 - val_accuracy: 0.7714\n",
            "Epoch 2117/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2907 - val_accuracy: 0.7714\n",
            "Epoch 2118/4000\n",
            "1/1 [==============================] - 0s 92ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 1.2912 - val_accuracy: 0.7714\n",
            "Epoch 2119/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 1.2919 - val_accuracy: 0.7714\n",
            "Epoch 2120/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 1.2926 - val_accuracy: 0.7714\n",
            "Epoch 2121/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 1.2932 - val_accuracy: 0.7571\n",
            "Epoch 2122/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 1.2936 - val_accuracy: 0.7571\n",
            "Epoch 2123/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 1.2941 - val_accuracy: 0.7571\n",
            "Epoch 2124/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2945 - val_accuracy: 0.7571\n",
            "Epoch 2125/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2948 - val_accuracy: 0.7714\n",
            "Epoch 2126/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2951 - val_accuracy: 0.7714\n",
            "Epoch 2127/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2956 - val_accuracy: 0.7714\n",
            "Epoch 2128/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2961 - val_accuracy: 0.7714\n",
            "Epoch 2129/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 1.2966 - val_accuracy: 0.7714\n",
            "Epoch 2130/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2972 - val_accuracy: 0.7714\n",
            "Epoch 2131/4000\n",
            "1/1 [==============================] - 0s 99ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2978 - val_accuracy: 0.7571\n",
            "Epoch 2132/4000\n",
            "1/1 [==============================] - 0s 109ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2984 - val_accuracy: 0.7571\n",
            "Epoch 2133/4000\n",
            "1/1 [==============================] - 0s 110ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2989 - val_accuracy: 0.7571\n",
            "Epoch 2134/4000\n",
            "1/1 [==============================] - 0s 104ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2993 - val_accuracy: 0.7571\n",
            "Epoch 2135/4000\n",
            "1/1 [==============================] - 0s 119ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 1.2995 - val_accuracy: 0.7714\n",
            "Epoch 2136/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.2999 - val_accuracy: 0.7714\n",
            "Epoch 2137/4000\n",
            "1/1 [==============================] - 0s 119ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.3003 - val_accuracy: 0.7714\n",
            "Epoch 2138/4000\n",
            "1/1 [==============================] - 0s 150ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.3007 - val_accuracy: 0.7714\n",
            "Epoch 2139/4000\n",
            "1/1 [==============================] - 0s 96ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.3012 - val_accuracy: 0.7714\n",
            "Epoch 2140/4000\n",
            "1/1 [==============================] - 0s 97ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.3018 - val_accuracy: 0.7714\n",
            "Epoch 2141/4000\n",
            "1/1 [==============================] - 0s 112ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 1.3026 - val_accuracy: 0.7714\n",
            "Epoch 2142/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3032 - val_accuracy: 0.7571\n",
            "Epoch 2143/4000\n",
            "1/1 [==============================] - 0s 118ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3037 - val_accuracy: 0.7571\n",
            "Epoch 2144/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3043 - val_accuracy: 0.7571\n",
            "Epoch 2145/4000\n",
            "1/1 [==============================] - 0s 96ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3047 - val_accuracy: 0.7571\n",
            "Epoch 2146/4000\n",
            "1/1 [==============================] - 0s 111ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3049 - val_accuracy: 0.7571\n",
            "Epoch 2147/4000\n",
            "1/1 [==============================] - 0s 115ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 1.3053 - val_accuracy: 0.7714\n",
            "Epoch 2148/4000\n",
            "1/1 [==============================] - 0s 153ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3057 - val_accuracy: 0.7714\n",
            "Epoch 2149/4000\n",
            "1/1 [==============================] - 0s 112ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3061 - val_accuracy: 0.7714\n",
            "Epoch 2150/4000\n",
            "1/1 [==============================] - 0s 99ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3066 - val_accuracy: 0.7714\n",
            "Epoch 2151/4000\n",
            "1/1 [==============================] - 0s 95ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3072 - val_accuracy: 0.7571\n",
            "Epoch 2152/4000\n",
            "1/1 [==============================] - 0s 93ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3078 - val_accuracy: 0.7571\n",
            "Epoch 2153/4000\n",
            "1/1 [==============================] - 0s 243ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 1.3083 - val_accuracy: 0.7571\n",
            "Epoch 2154/4000\n",
            "1/1 [==============================] - 0s 134ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3088 - val_accuracy: 0.7571\n",
            "Epoch 2155/4000\n",
            "1/1 [==============================] - 0s 225ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3092 - val_accuracy: 0.7571\n",
            "Epoch 2156/4000\n",
            "1/1 [==============================] - 0s 182ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3095 - val_accuracy: 0.7714\n",
            "Epoch 2157/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3099 - val_accuracy: 0.7714\n",
            "Epoch 2158/4000\n",
            "1/1 [==============================] - 0s 123ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3103 - val_accuracy: 0.7714\n",
            "Epoch 2159/4000\n",
            "1/1 [==============================] - 0s 135ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 1.3108 - val_accuracy: 0.7714\n",
            "Epoch 2160/4000\n",
            "1/1 [==============================] - 0s 126ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3113 - val_accuracy: 0.7714\n",
            "Epoch 2161/4000\n",
            "1/1 [==============================] - 0s 87ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3119 - val_accuracy: 0.7714\n",
            "Epoch 2162/4000\n",
            "1/1 [==============================] - 0s 171ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3126 - val_accuracy: 0.7571\n",
            "Epoch 2163/4000\n",
            "1/1 [==============================] - 0s 108ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3133 - val_accuracy: 0.7571\n",
            "Epoch 2164/4000\n",
            "1/1 [==============================] - 0s 135ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3137 - val_accuracy: 0.7571\n",
            "Epoch 2165/4000\n",
            "1/1 [==============================] - 0s 140ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 1.3140 - val_accuracy: 0.7571\n",
            "Epoch 2166/4000\n",
            "1/1 [==============================] - 0s 115ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3143 - val_accuracy: 0.7571\n",
            "Epoch 2167/4000\n",
            "1/1 [==============================] - 0s 138ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3146 - val_accuracy: 0.7714\n",
            "Epoch 2168/4000\n",
            "1/1 [==============================] - 0s 179ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3149 - val_accuracy: 0.7714\n",
            "Epoch 2169/4000\n",
            "1/1 [==============================] - 0s 156ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3153 - val_accuracy: 0.7714\n",
            "Epoch 2170/4000\n",
            "1/1 [==============================] - 0s 117ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3158 - val_accuracy: 0.7714\n",
            "Epoch 2171/4000\n",
            "1/1 [==============================] - 0s 94ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3164 - val_accuracy: 0.7714\n",
            "Epoch 2172/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 1.3170 - val_accuracy: 0.7714\n",
            "Epoch 2173/4000\n",
            "1/1 [==============================] - 0s 110ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3177 - val_accuracy: 0.7571\n",
            "Epoch 2174/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3183 - val_accuracy: 0.7571\n",
            "Epoch 2175/4000\n",
            "1/1 [==============================] - 0s 109ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3188 - val_accuracy: 0.7571\n",
            "Epoch 2176/4000\n",
            "1/1 [==============================] - 0s 189ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3192 - val_accuracy: 0.7571\n",
            "Epoch 2177/4000\n",
            "1/1 [==============================] - 0s 182ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3195 - val_accuracy: 0.7571\n",
            "Epoch 2178/4000\n",
            "1/1 [==============================] - 0s 160ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 1.3199 - val_accuracy: 0.7714\n",
            "Epoch 2179/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3203 - val_accuracy: 0.7714\n",
            "Epoch 2180/4000\n",
            "1/1 [==============================] - 0s 136ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3208 - val_accuracy: 0.7714\n",
            "Epoch 2181/4000\n",
            "1/1 [==============================] - 0s 136ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3214 - val_accuracy: 0.7714\n",
            "Epoch 2182/4000\n",
            "1/1 [==============================] - 0s 131ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3220 - val_accuracy: 0.7571\n",
            "Epoch 2183/4000\n",
            "1/1 [==============================] - 0s 107ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3225 - val_accuracy: 0.7571\n",
            "Epoch 2184/4000\n",
            "1/1 [==============================] - 0s 100ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 1.3231 - val_accuracy: 0.7571\n",
            "Epoch 2185/4000\n",
            "1/1 [==============================] - 0s 89ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3236 - val_accuracy: 0.7571\n",
            "Epoch 2186/4000\n",
            "1/1 [==============================] - 0s 143ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3239 - val_accuracy: 0.7571\n",
            "Epoch 2187/4000\n",
            "1/1 [==============================] - 0s 138ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3242 - val_accuracy: 0.7571\n",
            "Epoch 2188/4000\n",
            "1/1 [==============================] - 0s 116ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3245 - val_accuracy: 0.7571\n",
            "Epoch 2189/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3248 - val_accuracy: 0.7714\n",
            "Epoch 2190/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3251 - val_accuracy: 0.7714\n",
            "Epoch 2191/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 1.3257 - val_accuracy: 0.7714\n",
            "Epoch 2192/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3263 - val_accuracy: 0.7714\n",
            "Epoch 2193/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3270 - val_accuracy: 0.7571\n",
            "Epoch 2194/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3277 - val_accuracy: 0.7571\n",
            "Epoch 2195/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3283 - val_accuracy: 0.7571\n",
            "Epoch 2196/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3287 - val_accuracy: 0.7571\n",
            "Epoch 2197/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 1.3291 - val_accuracy: 0.7571\n",
            "Epoch 2198/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3294 - val_accuracy: 0.7571\n",
            "Epoch 2199/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3297 - val_accuracy: 0.7571\n",
            "Epoch 2200/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3300 - val_accuracy: 0.7714\n",
            "Epoch 2201/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3304 - val_accuracy: 0.7714\n",
            "Epoch 2202/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3310 - val_accuracy: 0.7714\n",
            "Epoch 2203/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3316 - val_accuracy: 0.7571\n",
            "Epoch 2204/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 1.3323 - val_accuracy: 0.7571\n",
            "Epoch 2205/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3329 - val_accuracy: 0.7571\n",
            "Epoch 2206/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3332 - val_accuracy: 0.7571\n",
            "Epoch 2207/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3336 - val_accuracy: 0.7571\n",
            "Epoch 2208/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3339 - val_accuracy: 0.7571\n",
            "Epoch 2209/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3342 - val_accuracy: 0.7571\n",
            "Epoch 2210/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 1.3345 - val_accuracy: 0.7714\n",
            "Epoch 2211/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3350 - val_accuracy: 0.7714\n",
            "Epoch 2212/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3355 - val_accuracy: 0.7714\n",
            "Epoch 2213/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3361 - val_accuracy: 0.7714\n",
            "Epoch 2214/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3367 - val_accuracy: 0.7571\n",
            "Epoch 2215/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3374 - val_accuracy: 0.7571\n",
            "Epoch 2216/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3380 - val_accuracy: 0.7571\n",
            "Epoch 2217/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 1.3385 - val_accuracy: 0.7571\n",
            "Epoch 2218/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3389 - val_accuracy: 0.7571\n",
            "Epoch 2219/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3392 - val_accuracy: 0.7571\n",
            "Epoch 2220/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3394 - val_accuracy: 0.7571\n",
            "Epoch 2221/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3398 - val_accuracy: 0.7571\n",
            "Epoch 2222/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3402 - val_accuracy: 0.7571\n",
            "Epoch 2223/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3407 - val_accuracy: 0.7571\n",
            "Epoch 2224/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 1.3412 - val_accuracy: 0.7571\n",
            "Epoch 2225/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3417 - val_accuracy: 0.7571\n",
            "Epoch 2226/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3423 - val_accuracy: 0.7571\n",
            "Epoch 2227/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3428 - val_accuracy: 0.7571\n",
            "Epoch 2228/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3432 - val_accuracy: 0.7571\n",
            "Epoch 2229/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3437 - val_accuracy: 0.7571\n",
            "Epoch 2230/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3440 - val_accuracy: 0.7571\n",
            "Epoch 2231/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 1.3443 - val_accuracy: 0.7571\n",
            "Epoch 2232/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3447 - val_accuracy: 0.7571\n",
            "Epoch 2233/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3452 - val_accuracy: 0.7571\n",
            "Epoch 2234/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3458 - val_accuracy: 0.7571\n",
            "Epoch 2235/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3465 - val_accuracy: 0.7571\n",
            "Epoch 2236/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3470 - val_accuracy: 0.7571\n",
            "Epoch 2237/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3476 - val_accuracy: 0.7571\n",
            "Epoch 2238/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 1.3481 - val_accuracy: 0.7571\n",
            "Epoch 2239/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3485 - val_accuracy: 0.7571\n",
            "Epoch 2240/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3488 - val_accuracy: 0.7571\n",
            "Epoch 2241/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3491 - val_accuracy: 0.7571\n",
            "Epoch 2242/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3494 - val_accuracy: 0.7571\n",
            "Epoch 2243/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3498 - val_accuracy: 0.7571\n",
            "Epoch 2244/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3502 - val_accuracy: 0.7571\n",
            "Epoch 2245/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 1.3508 - val_accuracy: 0.7571\n",
            "Epoch 2246/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3513 - val_accuracy: 0.7571\n",
            "Epoch 2247/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3519 - val_accuracy: 0.7571\n",
            "Epoch 2248/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3525 - val_accuracy: 0.7571\n",
            "Epoch 2249/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3530 - val_accuracy: 0.7571\n",
            "Epoch 2250/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3534 - val_accuracy: 0.7571\n",
            "Epoch 2251/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3537 - val_accuracy: 0.7571\n",
            "Epoch 2252/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 1.3541 - val_accuracy: 0.7571\n",
            "Epoch 2253/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3544 - val_accuracy: 0.7571\n",
            "Epoch 2254/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3549 - val_accuracy: 0.7571\n",
            "Epoch 2255/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3555 - val_accuracy: 0.7571\n",
            "Epoch 2256/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3561 - val_accuracy: 0.7571\n",
            "Epoch 2257/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3567 - val_accuracy: 0.7571\n",
            "Epoch 2258/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3572 - val_accuracy: 0.7571\n",
            "Epoch 2259/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 1.3576 - val_accuracy: 0.7571\n",
            "Epoch 2260/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3579 - val_accuracy: 0.7571\n",
            "Epoch 2261/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3582 - val_accuracy: 0.7571\n",
            "Epoch 2262/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3584 - val_accuracy: 0.7571\n",
            "Epoch 2263/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3587 - val_accuracy: 0.7571\n",
            "Epoch 2264/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3591 - val_accuracy: 0.7571\n",
            "Epoch 2265/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3596 - val_accuracy: 0.7571\n",
            "Epoch 2266/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3602 - val_accuracy: 0.7571\n",
            "Epoch 2267/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 1.3608 - val_accuracy: 0.7571\n",
            "Epoch 2268/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3614 - val_accuracy: 0.7571\n",
            "Epoch 2269/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3619 - val_accuracy: 0.7571\n",
            "Epoch 2270/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3623 - val_accuracy: 0.7571\n",
            "Epoch 2271/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3628 - val_accuracy: 0.7571\n",
            "Epoch 2272/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3632 - val_accuracy: 0.7571\n",
            "Epoch 2273/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3634 - val_accuracy: 0.7571\n",
            "Epoch 2274/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 1.3638 - val_accuracy: 0.7571\n",
            "Epoch 2275/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3642 - val_accuracy: 0.7571\n",
            "Epoch 2276/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3647 - val_accuracy: 0.7571\n",
            "Epoch 2277/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3653 - val_accuracy: 0.7571\n",
            "Epoch 2278/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3659 - val_accuracy: 0.7571\n",
            "Epoch 2279/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3664 - val_accuracy: 0.7571\n",
            "Epoch 2280/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3669 - val_accuracy: 0.7571\n",
            "Epoch 2281/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3672 - val_accuracy: 0.7571\n",
            "Epoch 2282/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 1.3677 - val_accuracy: 0.7571\n",
            "Epoch 2283/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3680 - val_accuracy: 0.7571\n",
            "Epoch 2284/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3683 - val_accuracy: 0.7571\n",
            "Epoch 2285/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3688 - val_accuracy: 0.7571\n",
            "Epoch 2286/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3693 - val_accuracy: 0.7571\n",
            "Epoch 2287/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3699 - val_accuracy: 0.7571\n",
            "Epoch 2288/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3705 - val_accuracy: 0.7571\n",
            "Epoch 2289/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 1.3710 - val_accuracy: 0.7571\n",
            "Epoch 2290/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3714 - val_accuracy: 0.7571\n",
            "Epoch 2291/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3719 - val_accuracy: 0.7571\n",
            "Epoch 2292/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3722 - val_accuracy: 0.7571\n",
            "Epoch 2293/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3726 - val_accuracy: 0.7571\n",
            "Epoch 2294/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3729 - val_accuracy: 0.7571\n",
            "Epoch 2295/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3733 - val_accuracy: 0.7571\n",
            "Epoch 2296/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3738 - val_accuracy: 0.7571\n",
            "Epoch 2297/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 1.3742 - val_accuracy: 0.7571\n",
            "Epoch 2298/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3747 - val_accuracy: 0.7571\n",
            "Epoch 2299/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3754 - val_accuracy: 0.7571\n",
            "Epoch 2300/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3760 - val_accuracy: 0.7571\n",
            "Epoch 2301/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3765 - val_accuracy: 0.7571\n",
            "Epoch 2302/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3767 - val_accuracy: 0.7571\n",
            "Epoch 2303/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3770 - val_accuracy: 0.7571\n",
            "Epoch 2304/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3772 - val_accuracy: 0.7571\n",
            "Epoch 2305/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 1.3776 - val_accuracy: 0.7571\n",
            "Epoch 2306/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3782 - val_accuracy: 0.7571\n",
            "Epoch 2307/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3787 - val_accuracy: 0.7571\n",
            "Epoch 2308/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3792 - val_accuracy: 0.7571\n",
            "Epoch 2309/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3798 - val_accuracy: 0.7571\n",
            "Epoch 2310/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3803 - val_accuracy: 0.7571\n",
            "Epoch 2311/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3809 - val_accuracy: 0.7571\n",
            "Epoch 2312/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3813 - val_accuracy: 0.7571\n",
            "Epoch 2313/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 1.3816 - val_accuracy: 0.7571\n",
            "Epoch 2314/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3819 - val_accuracy: 0.7571\n",
            "Epoch 2315/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3823 - val_accuracy: 0.7571\n",
            "Epoch 2316/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3827 - val_accuracy: 0.7571\n",
            "Epoch 2317/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3830 - val_accuracy: 0.7571\n",
            "Epoch 2318/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3834 - val_accuracy: 0.7571\n",
            "Epoch 2319/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3840 - val_accuracy: 0.7571\n",
            "Epoch 2320/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3845 - val_accuracy: 0.7571\n",
            "Epoch 2321/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 1.3851 - val_accuracy: 0.7571\n",
            "Epoch 2322/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3856 - val_accuracy: 0.7571\n",
            "Epoch 2323/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3860 - val_accuracy: 0.7571\n",
            "Epoch 2324/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3863 - val_accuracy: 0.7571\n",
            "Epoch 2325/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3867 - val_accuracy: 0.7571\n",
            "Epoch 2326/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3870 - val_accuracy: 0.7571\n",
            "Epoch 2327/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3874 - val_accuracy: 0.7571\n",
            "Epoch 2328/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3879 - val_accuracy: 0.7571\n",
            "Epoch 2329/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 1.3886 - val_accuracy: 0.7571\n",
            "Epoch 2330/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3892 - val_accuracy: 0.7571\n",
            "Epoch 2331/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3898 - val_accuracy: 0.7571\n",
            "Epoch 2332/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3903 - val_accuracy: 0.7571\n",
            "Epoch 2333/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3906 - val_accuracy: 0.7571\n",
            "Epoch 2334/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3910 - val_accuracy: 0.7571\n",
            "Epoch 2335/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3913 - val_accuracy: 0.7571\n",
            "Epoch 2336/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3916 - val_accuracy: 0.7571\n",
            "Epoch 2337/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 1.3920 - val_accuracy: 0.7571\n",
            "Epoch 2338/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3923 - val_accuracy: 0.7571\n",
            "Epoch 2339/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3927 - val_accuracy: 0.7571\n",
            "Epoch 2340/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3932 - val_accuracy: 0.7571\n",
            "Epoch 2341/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3937 - val_accuracy: 0.7571\n",
            "Epoch 2342/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3943 - val_accuracy: 0.7571\n",
            "Epoch 2343/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3948 - val_accuracy: 0.7571\n",
            "Epoch 2344/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3953 - val_accuracy: 0.7571\n",
            "Epoch 2345/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3956 - val_accuracy: 0.7571\n",
            "Epoch 2346/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 1.3959 - val_accuracy: 0.7571\n",
            "Epoch 2347/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3963 - val_accuracy: 0.7571\n",
            "Epoch 2348/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3968 - val_accuracy: 0.7571\n",
            "Epoch 2349/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3974 - val_accuracy: 0.7571\n",
            "Epoch 2350/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3980 - val_accuracy: 0.7571\n",
            "Epoch 2351/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3984 - val_accuracy: 0.7571\n",
            "Epoch 2352/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3989 - val_accuracy: 0.7571\n",
            "Epoch 2353/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3994 - val_accuracy: 0.7571\n",
            "Epoch 2354/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 1.3999 - val_accuracy: 0.7571\n",
            "Epoch 2355/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4002 - val_accuracy: 0.7571\n",
            "Epoch 2356/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4005 - val_accuracy: 0.7571\n",
            "Epoch 2357/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4008 - val_accuracy: 0.7571\n",
            "Epoch 2358/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4011 - val_accuracy: 0.7571\n",
            "Epoch 2359/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4016 - val_accuracy: 0.7571\n",
            "Epoch 2360/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4021 - val_accuracy: 0.7571\n",
            "Epoch 2361/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4026 - val_accuracy: 0.7571\n",
            "Epoch 2362/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4031 - val_accuracy: 0.7571\n",
            "Epoch 2363/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 1.4036 - val_accuracy: 0.7571\n",
            "Epoch 2364/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4041 - val_accuracy: 0.7571\n",
            "Epoch 2365/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4046 - val_accuracy: 0.7571\n",
            "Epoch 2366/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4051 - val_accuracy: 0.7571\n",
            "Epoch 2367/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4054 - val_accuracy: 0.7571\n",
            "Epoch 2368/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4056 - val_accuracy: 0.7571\n",
            "Epoch 2369/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4060 - val_accuracy: 0.7571\n",
            "Epoch 2370/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4066 - val_accuracy: 0.7571\n",
            "Epoch 2371/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4071 - val_accuracy: 0.7571\n",
            "Epoch 2372/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 1.4075 - val_accuracy: 0.7571\n",
            "Epoch 2373/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4079 - val_accuracy: 0.7571\n",
            "Epoch 2374/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4084 - val_accuracy: 0.7571\n",
            "Epoch 2375/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4089 - val_accuracy: 0.7571\n",
            "Epoch 2376/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4093 - val_accuracy: 0.7571\n",
            "Epoch 2377/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4096 - val_accuracy: 0.7571\n",
            "Epoch 2378/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4099 - val_accuracy: 0.7571\n",
            "Epoch 2379/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4101 - val_accuracy: 0.7571\n",
            "Epoch 2380/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4106 - val_accuracy: 0.7571\n",
            "Epoch 2381/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 1.4111 - val_accuracy: 0.7571\n",
            "Epoch 2382/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4116 - val_accuracy: 0.7571\n",
            "Epoch 2383/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4121 - val_accuracy: 0.7571\n",
            "Epoch 2384/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4126 - val_accuracy: 0.7571\n",
            "Epoch 2385/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4132 - val_accuracy: 0.7571\n",
            "Epoch 2386/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4138 - val_accuracy: 0.7571\n",
            "Epoch 2387/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4143 - val_accuracy: 0.7571\n",
            "Epoch 2388/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4145 - val_accuracy: 0.7571\n",
            "Epoch 2389/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4147 - val_accuracy: 0.7571\n",
            "Epoch 2390/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 1.4149 - val_accuracy: 0.7571\n",
            "Epoch 2391/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4153 - val_accuracy: 0.7571\n",
            "Epoch 2392/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4158 - val_accuracy: 0.7571\n",
            "Epoch 2393/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4163 - val_accuracy: 0.7571\n",
            "Epoch 2394/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4167 - val_accuracy: 0.7571\n",
            "Epoch 2395/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4172 - val_accuracy: 0.7571\n",
            "Epoch 2396/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4178 - val_accuracy: 0.7571\n",
            "Epoch 2397/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4184 - val_accuracy: 0.7571\n",
            "Epoch 2398/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4189 - val_accuracy: 0.7571\n",
            "Epoch 2399/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 1.4193 - val_accuracy: 0.7571\n",
            "Epoch 2400/4000\n",
            "1/1 [==============================] - 0s 90ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4196 - val_accuracy: 0.7571\n",
            "Epoch 2401/4000\n",
            "1/1 [==============================] - 0s 220ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4199 - val_accuracy: 0.7571\n",
            "Epoch 2402/4000\n",
            "1/1 [==============================] - 0s 163ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4204 - val_accuracy: 0.7571\n",
            "Epoch 2403/4000\n",
            "1/1 [==============================] - 0s 107ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4209 - val_accuracy: 0.7571\n",
            "Epoch 2404/4000\n",
            "1/1 [==============================] - 0s 117ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4214 - val_accuracy: 0.7571\n",
            "Epoch 2405/4000\n",
            "1/1 [==============================] - 0s 266ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4218 - val_accuracy: 0.7571\n",
            "Epoch 2406/4000\n",
            "1/1 [==============================] - 0s 156ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4223 - val_accuracy: 0.7571\n",
            "Epoch 2407/4000\n",
            "1/1 [==============================] - 0s 149ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4227 - val_accuracy: 0.7571\n",
            "Epoch 2408/4000\n",
            "1/1 [==============================] - 0s 109ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 1.4231 - val_accuracy: 0.7571\n",
            "Epoch 2409/4000\n",
            "1/1 [==============================] - 0s 223ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4235 - val_accuracy: 0.7571\n",
            "Epoch 2410/4000\n",
            "1/1 [==============================] - 0s 225ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4238 - val_accuracy: 0.7571\n",
            "Epoch 2411/4000\n",
            "1/1 [==============================] - 0s 155ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4240 - val_accuracy: 0.7571\n",
            "Epoch 2412/4000\n",
            "1/1 [==============================] - 0s 92ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4244 - val_accuracy: 0.7571\n",
            "Epoch 2413/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4249 - val_accuracy: 0.7571\n",
            "Epoch 2414/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4255 - val_accuracy: 0.7571\n",
            "Epoch 2415/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4259 - val_accuracy: 0.7571\n",
            "Epoch 2416/4000\n",
            "1/1 [==============================] - 0s 125ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4265 - val_accuracy: 0.7571\n",
            "Epoch 2417/4000\n",
            "1/1 [==============================] - 0s 123ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 1.4270 - val_accuracy: 0.7571\n",
            "Epoch 2418/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4275 - val_accuracy: 0.7571\n",
            "Epoch 2419/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4280 - val_accuracy: 0.7571\n",
            "Epoch 2420/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4283 - val_accuracy: 0.7571\n",
            "Epoch 2421/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4286 - val_accuracy: 0.7571\n",
            "Epoch 2422/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4289 - val_accuracy: 0.7571\n",
            "Epoch 2423/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4294 - val_accuracy: 0.7571\n",
            "Epoch 2424/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4298 - val_accuracy: 0.7571\n",
            "Epoch 2425/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4303 - val_accuracy: 0.7571\n",
            "Epoch 2426/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4308 - val_accuracy: 0.7571\n",
            "Epoch 2427/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 1.4314 - val_accuracy: 0.7571\n",
            "Epoch 2428/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4319 - val_accuracy: 0.7571\n",
            "Epoch 2429/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4323 - val_accuracy: 0.7571\n",
            "Epoch 2430/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4326 - val_accuracy: 0.7571\n",
            "Epoch 2431/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4329 - val_accuracy: 0.7571\n",
            "Epoch 2432/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4332 - val_accuracy: 0.7571\n",
            "Epoch 2433/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4335 - val_accuracy: 0.7571\n",
            "Epoch 2434/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4339 - val_accuracy: 0.7571\n",
            "Epoch 2435/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4344 - val_accuracy: 0.7571\n",
            "Epoch 2436/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4349 - val_accuracy: 0.7571\n",
            "Epoch 2437/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 1.4354 - val_accuracy: 0.7571\n",
            "Epoch 2438/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4359 - val_accuracy: 0.7571\n",
            "Epoch 2439/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4365 - val_accuracy: 0.7571\n",
            "Epoch 2440/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4369 - val_accuracy: 0.7571\n",
            "Epoch 2441/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4372 - val_accuracy: 0.7571\n",
            "Epoch 2442/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4375 - val_accuracy: 0.7571\n",
            "Epoch 2443/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4379 - val_accuracy: 0.7571\n",
            "Epoch 2444/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4382 - val_accuracy: 0.7571\n",
            "Epoch 2445/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4386 - val_accuracy: 0.7571\n",
            "Epoch 2446/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4391 - val_accuracy: 0.7571\n",
            "Epoch 2447/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 1.4396 - val_accuracy: 0.7571\n",
            "Epoch 2448/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4401 - val_accuracy: 0.7571\n",
            "Epoch 2449/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4407 - val_accuracy: 0.7571\n",
            "Epoch 2450/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4412 - val_accuracy: 0.7571\n",
            "Epoch 2451/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4417 - val_accuracy: 0.7571\n",
            "Epoch 2452/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4420 - val_accuracy: 0.7571\n",
            "Epoch 2453/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4422 - val_accuracy: 0.7571\n",
            "Epoch 2454/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4425 - val_accuracy: 0.7571\n",
            "Epoch 2455/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4428 - val_accuracy: 0.7571\n",
            "Epoch 2456/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4433 - val_accuracy: 0.7571\n",
            "Epoch 2457/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 1.4438 - val_accuracy: 0.7571\n",
            "Epoch 2458/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4442 - val_accuracy: 0.7571\n",
            "Epoch 2459/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4448 - val_accuracy: 0.7571\n",
            "Epoch 2460/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4454 - val_accuracy: 0.7571\n",
            "Epoch 2461/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4458 - val_accuracy: 0.7571\n",
            "Epoch 2462/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4462 - val_accuracy: 0.7571\n",
            "Epoch 2463/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4466 - val_accuracy: 0.7571\n",
            "Epoch 2464/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4469 - val_accuracy: 0.7571\n",
            "Epoch 2465/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4473 - val_accuracy: 0.7571\n",
            "Epoch 2466/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4477 - val_accuracy: 0.7571\n",
            "Epoch 2467/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 1.4482 - val_accuracy: 0.7571\n",
            "Epoch 2468/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4486 - val_accuracy: 0.7571\n",
            "Epoch 2469/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4490 - val_accuracy: 0.7571\n",
            "Epoch 2470/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4496 - val_accuracy: 0.7571\n",
            "Epoch 2471/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4501 - val_accuracy: 0.7571\n",
            "Epoch 2472/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4506 - val_accuracy: 0.7571\n",
            "Epoch 2473/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4509 - val_accuracy: 0.7571\n",
            "Epoch 2474/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4511 - val_accuracy: 0.7571\n",
            "Epoch 2475/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4515 - val_accuracy: 0.7571\n",
            "Epoch 2476/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4519 - val_accuracy: 0.7571\n",
            "Epoch 2477/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 1.4524 - val_accuracy: 0.7571\n",
            "Epoch 2478/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4528 - val_accuracy: 0.7571\n",
            "Epoch 2479/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4532 - val_accuracy: 0.7571\n",
            "Epoch 2480/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4537 - val_accuracy: 0.7571\n",
            "Epoch 2481/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4543 - val_accuracy: 0.7571\n",
            "Epoch 2482/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4548 - val_accuracy: 0.7571\n",
            "Epoch 2483/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4551 - val_accuracy: 0.7571\n",
            "Epoch 2484/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4554 - val_accuracy: 0.7571\n",
            "Epoch 2485/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4557 - val_accuracy: 0.7571\n",
            "Epoch 2486/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4562 - val_accuracy: 0.7571\n",
            "Epoch 2487/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4567 - val_accuracy: 0.7571\n",
            "Epoch 2488/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 1.4571 - val_accuracy: 0.7571\n",
            "Epoch 2489/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4576 - val_accuracy: 0.7571\n",
            "Epoch 2490/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4580 - val_accuracy: 0.7571\n",
            "Epoch 2491/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4585 - val_accuracy: 0.7571\n",
            "Epoch 2492/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4590 - val_accuracy: 0.7571\n",
            "Epoch 2493/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4592 - val_accuracy: 0.7571\n",
            "Epoch 2494/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4594 - val_accuracy: 0.7571\n",
            "Epoch 2495/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4597 - val_accuracy: 0.7571\n",
            "Epoch 2496/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4601 - val_accuracy: 0.7571\n",
            "Epoch 2497/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4605 - val_accuracy: 0.7571\n",
            "Epoch 2498/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 1.4609 - val_accuracy: 0.7571\n",
            "Epoch 2499/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4615 - val_accuracy: 0.7571\n",
            "Epoch 2500/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4620 - val_accuracy: 0.7571\n",
            "Epoch 2501/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4625 - val_accuracy: 0.7571\n",
            "Epoch 2502/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4630 - val_accuracy: 0.7571\n",
            "Epoch 2503/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4633 - val_accuracy: 0.7571\n",
            "Epoch 2504/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4636 - val_accuracy: 0.7571\n",
            "Epoch 2505/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4639 - val_accuracy: 0.7571\n",
            "Epoch 2506/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4643 - val_accuracy: 0.7571\n",
            "Epoch 2507/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4647 - val_accuracy: 0.7571\n",
            "Epoch 2508/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4652 - val_accuracy: 0.7571\n",
            "Epoch 2509/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 1.4657 - val_accuracy: 0.7571\n",
            "Epoch 2510/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4662 - val_accuracy: 0.7571\n",
            "Epoch 2511/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4667 - val_accuracy: 0.7571\n",
            "Epoch 2512/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4672 - val_accuracy: 0.7571\n",
            "Epoch 2513/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4675 - val_accuracy: 0.7571\n",
            "Epoch 2514/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4678 - val_accuracy: 0.7571\n",
            "Epoch 2515/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4680 - val_accuracy: 0.7571\n",
            "Epoch 2516/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4682 - val_accuracy: 0.7571\n",
            "Epoch 2517/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4685 - val_accuracy: 0.7571\n",
            "Epoch 2518/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4688 - val_accuracy: 0.7571\n",
            "Epoch 2519/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4694 - val_accuracy: 0.7571\n",
            "Epoch 2520/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4700 - val_accuracy: 0.7571\n",
            "Epoch 2521/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 1.4706 - val_accuracy: 0.7571\n",
            "Epoch 2522/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4712 - val_accuracy: 0.7571\n",
            "Epoch 2523/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4717 - val_accuracy: 0.7571\n",
            "Epoch 2524/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4721 - val_accuracy: 0.7571\n",
            "Epoch 2525/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4725 - val_accuracy: 0.7571\n",
            "Epoch 2526/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4728 - val_accuracy: 0.7571\n",
            "Epoch 2527/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4731 - val_accuracy: 0.7571\n",
            "Epoch 2528/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4734 - val_accuracy: 0.7571\n",
            "Epoch 2529/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4737 - val_accuracy: 0.7571\n",
            "Epoch 2530/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4742 - val_accuracy: 0.7571\n",
            "Epoch 2531/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4747 - val_accuracy: 0.7571\n",
            "Epoch 2532/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 1.4753 - val_accuracy: 0.7571\n",
            "Epoch 2533/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4757 - val_accuracy: 0.7571\n",
            "Epoch 2534/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4761 - val_accuracy: 0.7571\n",
            "Epoch 2535/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4764 - val_accuracy: 0.7571\n",
            "Epoch 2536/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4766 - val_accuracy: 0.7571\n",
            "Epoch 2537/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4769 - val_accuracy: 0.7571\n",
            "Epoch 2538/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4772 - val_accuracy: 0.7571\n",
            "Epoch 2539/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4776 - val_accuracy: 0.7571\n",
            "Epoch 2540/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4781 - val_accuracy: 0.7571\n",
            "Epoch 2541/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4785 - val_accuracy: 0.7571\n",
            "Epoch 2542/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4790 - val_accuracy: 0.7571\n",
            "Epoch 2543/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 1.4796 - val_accuracy: 0.7571\n",
            "Epoch 2544/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4802 - val_accuracy: 0.7571\n",
            "Epoch 2545/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4807 - val_accuracy: 0.7571\n",
            "Epoch 2546/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4809 - val_accuracy: 0.7571\n",
            "Epoch 2547/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4811 - val_accuracy: 0.7571\n",
            "Epoch 2548/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4815 - val_accuracy: 0.7571\n",
            "Epoch 2549/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4821 - val_accuracy: 0.7571\n",
            "Epoch 2550/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4828 - val_accuracy: 0.7571\n",
            "Epoch 2551/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4834 - val_accuracy: 0.7571\n",
            "Epoch 2552/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4839 - val_accuracy: 0.7571\n",
            "Epoch 2553/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4844 - val_accuracy: 0.7571\n",
            "Epoch 2554/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4850 - val_accuracy: 0.7571\n",
            "Epoch 2555/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 1.4856 - val_accuracy: 0.7571\n",
            "Epoch 2556/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4861 - val_accuracy: 0.7571\n",
            "Epoch 2557/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4863 - val_accuracy: 0.7571\n",
            "Epoch 2558/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4864 - val_accuracy: 0.7571\n",
            "Epoch 2559/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4866 - val_accuracy: 0.7571\n",
            "Epoch 2560/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4870 - val_accuracy: 0.7571\n",
            "Epoch 2561/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4875 - val_accuracy: 0.7571\n",
            "Epoch 2562/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4880 - val_accuracy: 0.7571\n",
            "Epoch 2563/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4886 - val_accuracy: 0.7571\n",
            "Epoch 2564/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4890 - val_accuracy: 0.7571\n",
            "Epoch 2565/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4894 - val_accuracy: 0.7571\n",
            "Epoch 2566/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4898 - val_accuracy: 0.7571\n",
            "Epoch 2567/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 1.4902 - val_accuracy: 0.7571\n",
            "Epoch 2568/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4905 - val_accuracy: 0.7571\n",
            "Epoch 2569/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4908 - val_accuracy: 0.7571\n",
            "Epoch 2570/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4912 - val_accuracy: 0.7571\n",
            "Epoch 2571/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4917 - val_accuracy: 0.7571\n",
            "Epoch 2572/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4922 - val_accuracy: 0.7571\n",
            "Epoch 2573/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4927 - val_accuracy: 0.7571\n",
            "Epoch 2574/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4931 - val_accuracy: 0.7571\n",
            "Epoch 2575/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4936 - val_accuracy: 0.7571\n",
            "Epoch 2576/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4940 - val_accuracy: 0.7714\n",
            "Epoch 2577/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4944 - val_accuracy: 0.7714\n",
            "Epoch 2578/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4948 - val_accuracy: 0.7714\n",
            "Epoch 2579/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 1.4952 - val_accuracy: 0.7714\n",
            "Epoch 2580/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4957 - val_accuracy: 0.7714\n",
            "Epoch 2581/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4960 - val_accuracy: 0.7714\n",
            "Epoch 2582/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4963 - val_accuracy: 0.7714\n",
            "Epoch 2583/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4966 - val_accuracy: 0.7714\n",
            "Epoch 2584/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4970 - val_accuracy: 0.7714\n",
            "Epoch 2585/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4974 - val_accuracy: 0.7714\n",
            "Epoch 2586/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4978 - val_accuracy: 0.7714\n",
            "Epoch 2587/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4983 - val_accuracy: 0.7714\n",
            "Epoch 2588/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4986 - val_accuracy: 0.7714\n",
            "Epoch 2589/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4990 - val_accuracy: 0.7714\n",
            "Epoch 2590/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4994 - val_accuracy: 0.7714\n",
            "Epoch 2591/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 1.4998 - val_accuracy: 0.7714\n",
            "Epoch 2592/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5002 - val_accuracy: 0.7714\n",
            "Epoch 2593/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5006 - val_accuracy: 0.7714\n",
            "Epoch 2594/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5009 - val_accuracy: 0.7714\n",
            "Epoch 2595/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5013 - val_accuracy: 0.7714\n",
            "Epoch 2596/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5017 - val_accuracy: 0.7714\n",
            "Epoch 2597/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5022 - val_accuracy: 0.7714\n",
            "Epoch 2598/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5026 - val_accuracy: 0.7714\n",
            "Epoch 2599/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5029 - val_accuracy: 0.7714\n",
            "Epoch 2600/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5033 - val_accuracy: 0.7714\n",
            "Epoch 2601/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5038 - val_accuracy: 0.7714\n",
            "Epoch 2602/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5042 - val_accuracy: 0.7714\n",
            "Epoch 2603/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5046 - val_accuracy: 0.7714\n",
            "Epoch 2604/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 1.5050 - val_accuracy: 0.7714\n",
            "Epoch 2605/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5053 - val_accuracy: 0.7714\n",
            "Epoch 2606/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5056 - val_accuracy: 0.7714\n",
            "Epoch 2607/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5060 - val_accuracy: 0.7714\n",
            "Epoch 2608/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5064 - val_accuracy: 0.7714\n",
            "Epoch 2609/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5069 - val_accuracy: 0.7714\n",
            "Epoch 2610/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5073 - val_accuracy: 0.7714\n",
            "Epoch 2611/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5076 - val_accuracy: 0.7714\n",
            "Epoch 2612/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5079 - val_accuracy: 0.7714\n",
            "Epoch 2613/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5083 - val_accuracy: 0.7714\n",
            "Epoch 2614/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5086 - val_accuracy: 0.7714\n",
            "Epoch 2615/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5089 - val_accuracy: 0.7714\n",
            "Epoch 2616/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 1.5093 - val_accuracy: 0.7714\n",
            "Epoch 2617/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5097 - val_accuracy: 0.7714\n",
            "Epoch 2618/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5101 - val_accuracy: 0.7714\n",
            "Epoch 2619/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5106 - val_accuracy: 0.7714\n",
            "Epoch 2620/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5111 - val_accuracy: 0.7714\n",
            "Epoch 2621/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5116 - val_accuracy: 0.7714\n",
            "Epoch 2622/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5121 - val_accuracy: 0.7714\n",
            "Epoch 2623/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5125 - val_accuracy: 0.7714\n",
            "Epoch 2624/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5128 - val_accuracy: 0.7714\n",
            "Epoch 2625/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5131 - val_accuracy: 0.7714\n",
            "Epoch 2626/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5135 - val_accuracy: 0.7714\n",
            "Epoch 2627/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5138 - val_accuracy: 0.7714\n",
            "Epoch 2628/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5141 - val_accuracy: 0.7714\n",
            "Epoch 2629/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 1.5146 - val_accuracy: 0.7714\n",
            "Epoch 2630/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5150 - val_accuracy: 0.7714\n",
            "Epoch 2631/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5155 - val_accuracy: 0.7714\n",
            "Epoch 2632/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5160 - val_accuracy: 0.7714\n",
            "Epoch 2633/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5163 - val_accuracy: 0.7714\n",
            "Epoch 2634/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5166 - val_accuracy: 0.7714\n",
            "Epoch 2635/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5169 - val_accuracy: 0.7714\n",
            "Epoch 2636/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5172 - val_accuracy: 0.7714\n",
            "Epoch 2637/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5177 - val_accuracy: 0.7714\n",
            "Epoch 2638/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5180 - val_accuracy: 0.7714\n",
            "Epoch 2639/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5184 - val_accuracy: 0.7714\n",
            "Epoch 2640/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5189 - val_accuracy: 0.7714\n",
            "Epoch 2641/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5194 - val_accuracy: 0.7714\n",
            "Epoch 2642/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5198 - val_accuracy: 0.7714\n",
            "Epoch 2643/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 1.5203 - val_accuracy: 0.7714\n",
            "Epoch 2644/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5207 - val_accuracy: 0.7714\n",
            "Epoch 2645/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5211 - val_accuracy: 0.7714\n",
            "Epoch 2646/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5215 - val_accuracy: 0.7714\n",
            "Epoch 2647/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5219 - val_accuracy: 0.7714\n",
            "Epoch 2648/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5223 - val_accuracy: 0.7714\n",
            "Epoch 2649/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5225 - val_accuracy: 0.7714\n",
            "Epoch 2650/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5229 - val_accuracy: 0.7714\n",
            "Epoch 2651/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5233 - val_accuracy: 0.7714\n",
            "Epoch 2652/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5238 - val_accuracy: 0.7714\n",
            "Epoch 2653/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5243 - val_accuracy: 0.7714\n",
            "Epoch 2654/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5247 - val_accuracy: 0.7714\n",
            "Epoch 2655/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5251 - val_accuracy: 0.7714\n",
            "Epoch 2656/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 1.5253 - val_accuracy: 0.7714\n",
            "Epoch 2657/4000\n",
            "1/1 [==============================] - 0s 37ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5257 - val_accuracy: 0.7714\n",
            "Epoch 2658/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5263 - val_accuracy: 0.7714\n",
            "Epoch 2659/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5269 - val_accuracy: 0.7714\n",
            "Epoch 2660/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5273 - val_accuracy: 0.7714\n",
            "Epoch 2661/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5278 - val_accuracy: 0.7714\n",
            "Epoch 2662/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5283 - val_accuracy: 0.7714\n",
            "Epoch 2663/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5289 - val_accuracy: 0.7714\n",
            "Epoch 2664/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5295 - val_accuracy: 0.7714\n",
            "Epoch 2665/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5300 - val_accuracy: 0.7714\n",
            "Epoch 2666/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5303 - val_accuracy: 0.7714\n",
            "Epoch 2667/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5305 - val_accuracy: 0.7714\n",
            "Epoch 2668/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5308 - val_accuracy: 0.7714\n",
            "Epoch 2669/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5311 - val_accuracy: 0.7714\n",
            "Epoch 2670/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 1.5316 - val_accuracy: 0.7714\n",
            "Epoch 2671/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5321 - val_accuracy: 0.7714\n",
            "Epoch 2672/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5327 - val_accuracy: 0.7714\n",
            "Epoch 2673/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5330 - val_accuracy: 0.7714\n",
            "Epoch 2674/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5333 - val_accuracy: 0.7714\n",
            "Epoch 2675/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5338 - val_accuracy: 0.7714\n",
            "Epoch 2676/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5343 - val_accuracy: 0.7714\n",
            "Epoch 2677/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5348 - val_accuracy: 0.7714\n",
            "Epoch 2678/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5351 - val_accuracy: 0.7714\n",
            "Epoch 2679/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5353 - val_accuracy: 0.7714\n",
            "Epoch 2680/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5356 - val_accuracy: 0.7714\n",
            "Epoch 2681/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5360 - val_accuracy: 0.7714\n",
            "Epoch 2682/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5366 - val_accuracy: 0.7714\n",
            "Epoch 2683/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5371 - val_accuracy: 0.7714\n",
            "Epoch 2684/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5375 - val_accuracy: 0.7714\n",
            "Epoch 2685/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 1.5377 - val_accuracy: 0.7714\n",
            "Epoch 2686/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5381 - val_accuracy: 0.7714\n",
            "Epoch 2687/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5386 - val_accuracy: 0.7714\n",
            "Epoch 2688/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5391 - val_accuracy: 0.7714\n",
            "Epoch 2689/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5394 - val_accuracy: 0.7714\n",
            "Epoch 2690/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5397 - val_accuracy: 0.7714\n",
            "Epoch 2691/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5401 - val_accuracy: 0.7714\n",
            "Epoch 2692/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5406 - val_accuracy: 0.7714\n",
            "Epoch 2693/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5411 - val_accuracy: 0.7714\n",
            "Epoch 2694/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5416 - val_accuracy: 0.7714\n",
            "Epoch 2695/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5419 - val_accuracy: 0.7714\n",
            "Epoch 2696/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5421 - val_accuracy: 0.7714\n",
            "Epoch 2697/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5424 - val_accuracy: 0.7714\n",
            "Epoch 2698/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5427 - val_accuracy: 0.7714\n",
            "Epoch 2699/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 1.5432 - val_accuracy: 0.7714\n",
            "Epoch 2700/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5436 - val_accuracy: 0.7714\n",
            "Epoch 2701/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5440 - val_accuracy: 0.7714\n",
            "Epoch 2702/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5445 - val_accuracy: 0.7714\n",
            "Epoch 2703/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5449 - val_accuracy: 0.7714\n",
            "Epoch 2704/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5454 - val_accuracy: 0.7714\n",
            "Epoch 2705/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5457 - val_accuracy: 0.7714\n",
            "Epoch 2706/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5461 - val_accuracy: 0.7714\n",
            "Epoch 2707/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5465 - val_accuracy: 0.7714\n",
            "Epoch 2708/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5469 - val_accuracy: 0.7714\n",
            "Epoch 2709/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5473 - val_accuracy: 0.7714\n",
            "Epoch 2710/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5477 - val_accuracy: 0.7714\n",
            "Epoch 2711/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5480 - val_accuracy: 0.7714\n",
            "Epoch 2712/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5485 - val_accuracy: 0.7714\n",
            "Epoch 2713/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5490 - val_accuracy: 0.7714\n",
            "Epoch 2714/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 1.5495 - val_accuracy: 0.7714\n",
            "Epoch 2715/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5498 - val_accuracy: 0.7714\n",
            "Epoch 2716/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5499 - val_accuracy: 0.7714\n",
            "Epoch 2717/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5501 - val_accuracy: 0.7714\n",
            "Epoch 2718/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5504 - val_accuracy: 0.7714\n",
            "Epoch 2719/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5508 - val_accuracy: 0.7714\n",
            "Epoch 2720/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5512 - val_accuracy: 0.7714\n",
            "Epoch 2721/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5516 - val_accuracy: 0.7714\n",
            "Epoch 2722/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5520 - val_accuracy: 0.7714\n",
            "Epoch 2723/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5525 - val_accuracy: 0.7714\n",
            "Epoch 2724/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5531 - val_accuracy: 0.7714\n",
            "Epoch 2725/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5537 - val_accuracy: 0.7714\n",
            "Epoch 2726/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5541 - val_accuracy: 0.7714\n",
            "Epoch 2727/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5544 - val_accuracy: 0.7714\n",
            "Epoch 2728/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5545 - val_accuracy: 0.7714\n",
            "Epoch 2729/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 1.5548 - val_accuracy: 0.7714\n",
            "Epoch 2730/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5551 - val_accuracy: 0.7714\n",
            "Epoch 2731/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5555 - val_accuracy: 0.7714\n",
            "Epoch 2732/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5559 - val_accuracy: 0.7714\n",
            "Epoch 2733/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5564 - val_accuracy: 0.7714\n",
            "Epoch 2734/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5569 - val_accuracy: 0.7714\n",
            "Epoch 2735/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5576 - val_accuracy: 0.7714\n",
            "Epoch 2736/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5582 - val_accuracy: 0.7714\n",
            "Epoch 2737/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5586 - val_accuracy: 0.7714\n",
            "Epoch 2738/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5587 - val_accuracy: 0.7714\n",
            "Epoch 2739/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5589 - val_accuracy: 0.7714\n",
            "Epoch 2740/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5592 - val_accuracy: 0.7714\n",
            "Epoch 2741/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5595 - val_accuracy: 0.7714\n",
            "Epoch 2742/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5598 - val_accuracy: 0.7714\n",
            "Epoch 2743/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5602 - val_accuracy: 0.7714\n",
            "Epoch 2744/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 1.5606 - val_accuracy: 0.7714\n",
            "Epoch 2745/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5611 - val_accuracy: 0.7714\n",
            "Epoch 2746/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5618 - val_accuracy: 0.7714\n",
            "Epoch 2747/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5623 - val_accuracy: 0.7714\n",
            "Epoch 2748/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5626 - val_accuracy: 0.7714\n",
            "Epoch 2749/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5628 - val_accuracy: 0.7714\n",
            "Epoch 2750/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5630 - val_accuracy: 0.7714\n",
            "Epoch 2751/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5633 - val_accuracy: 0.7714\n",
            "Epoch 2752/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5636 - val_accuracy: 0.7714\n",
            "Epoch 2753/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5640 - val_accuracy: 0.7714\n",
            "Epoch 2754/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5644 - val_accuracy: 0.7714\n",
            "Epoch 2755/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5649 - val_accuracy: 0.7714\n",
            "Epoch 2756/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5655 - val_accuracy: 0.7714\n",
            "Epoch 2757/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5661 - val_accuracy: 0.7714\n",
            "Epoch 2758/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5666 - val_accuracy: 0.7714\n",
            "Epoch 2759/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5668 - val_accuracy: 0.7714\n",
            "Epoch 2760/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 1.5670 - val_accuracy: 0.7714\n",
            "Epoch 2761/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5673 - val_accuracy: 0.7714\n",
            "Epoch 2762/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5677 - val_accuracy: 0.7714\n",
            "Epoch 2763/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5680 - val_accuracy: 0.7714\n",
            "Epoch 2764/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5684 - val_accuracy: 0.7714\n",
            "Epoch 2765/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5688 - val_accuracy: 0.7714\n",
            "Epoch 2766/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5693 - val_accuracy: 0.7714\n",
            "Epoch 2767/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5698 - val_accuracy: 0.7714\n",
            "Epoch 2768/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5703 - val_accuracy: 0.7714\n",
            "Epoch 2769/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5707 - val_accuracy: 0.7714\n",
            "Epoch 2770/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5709 - val_accuracy: 0.7714\n",
            "Epoch 2771/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5711 - val_accuracy: 0.7714\n",
            "Epoch 2772/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5714 - val_accuracy: 0.7714\n",
            "Epoch 2773/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5718 - val_accuracy: 0.7714\n",
            "Epoch 2774/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5722 - val_accuracy: 0.7714\n",
            "Epoch 2775/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5726 - val_accuracy: 0.7714\n",
            "Epoch 2776/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 1.5731 - val_accuracy: 0.7714\n",
            "Epoch 2777/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5737 - val_accuracy: 0.7714\n",
            "Epoch 2778/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5742 - val_accuracy: 0.7714\n",
            "Epoch 2779/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5747 - val_accuracy: 0.7714\n",
            "Epoch 2780/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5749 - val_accuracy: 0.7714\n",
            "Epoch 2781/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5752 - val_accuracy: 0.7714\n",
            "Epoch 2782/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5754 - val_accuracy: 0.7714\n",
            "Epoch 2783/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5757 - val_accuracy: 0.7714\n",
            "Epoch 2784/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5760 - val_accuracy: 0.7714\n",
            "Epoch 2785/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5764 - val_accuracy: 0.7714\n",
            "Epoch 2786/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5769 - val_accuracy: 0.7714\n",
            "Epoch 2787/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5774 - val_accuracy: 0.7714\n",
            "Epoch 2788/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5779 - val_accuracy: 0.7714\n",
            "Epoch 2789/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5783 - val_accuracy: 0.7714\n",
            "Epoch 2790/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5787 - val_accuracy: 0.7714\n",
            "Epoch 2791/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5790 - val_accuracy: 0.7714\n",
            "Epoch 2792/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5793 - val_accuracy: 0.7714\n",
            "Epoch 2793/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 1.5796 - val_accuracy: 0.7714\n",
            "Epoch 2794/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5799 - val_accuracy: 0.7714\n",
            "Epoch 2795/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5803 - val_accuracy: 0.7714\n",
            "Epoch 2796/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5807 - val_accuracy: 0.7714\n",
            "Epoch 2797/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5812 - val_accuracy: 0.7714\n",
            "Epoch 2798/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5818 - val_accuracy: 0.7714\n",
            "Epoch 2799/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5823 - val_accuracy: 0.7714\n",
            "Epoch 2800/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5826 - val_accuracy: 0.7714\n",
            "Epoch 2801/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5828 - val_accuracy: 0.7714\n",
            "Epoch 2802/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5831 - val_accuracy: 0.7714\n",
            "Epoch 2803/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5835 - val_accuracy: 0.7714\n",
            "Epoch 2804/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5839 - val_accuracy: 0.7714\n",
            "Epoch 2805/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5842 - val_accuracy: 0.7714\n",
            "Epoch 2806/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5845 - val_accuracy: 0.7714\n",
            "Epoch 2807/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5849 - val_accuracy: 0.7714\n",
            "Epoch 2808/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5854 - val_accuracy: 0.7714\n",
            "Epoch 2809/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5859 - val_accuracy: 0.7714\n",
            "Epoch 2810/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 1.5864 - val_accuracy: 0.7714\n",
            "Epoch 2811/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5867 - val_accuracy: 0.7714\n",
            "Epoch 2812/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5869 - val_accuracy: 0.7714\n",
            "Epoch 2813/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5871 - val_accuracy: 0.7714\n",
            "Epoch 2814/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5874 - val_accuracy: 0.7714\n",
            "Epoch 2815/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5878 - val_accuracy: 0.7714\n",
            "Epoch 2816/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5882 - val_accuracy: 0.7714\n",
            "Epoch 2817/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5887 - val_accuracy: 0.7714\n",
            "Epoch 2818/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5892 - val_accuracy: 0.7714\n",
            "Epoch 2819/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5898 - val_accuracy: 0.7714\n",
            "Epoch 2820/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5904 - val_accuracy: 0.7714\n",
            "Epoch 2821/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5909 - val_accuracy: 0.7714\n",
            "Epoch 2822/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5911 - val_accuracy: 0.7714\n",
            "Epoch 2823/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5913 - val_accuracy: 0.7714\n",
            "Epoch 2824/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5916 - val_accuracy: 0.7714\n",
            "Epoch 2825/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5918 - val_accuracy: 0.7714\n",
            "Epoch 2826/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5920 - val_accuracy: 0.7714\n",
            "Epoch 2827/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 1.5923 - val_accuracy: 0.7714\n",
            "Epoch 2828/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5927 - val_accuracy: 0.7714\n",
            "Epoch 2829/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5932 - val_accuracy: 0.7714\n",
            "Epoch 2830/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5938 - val_accuracy: 0.7714\n",
            "Epoch 2831/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5944 - val_accuracy: 0.7714\n",
            "Epoch 2832/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5948 - val_accuracy: 0.7714\n",
            "Epoch 2833/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5951 - val_accuracy: 0.7714\n",
            "Epoch 2834/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5953 - val_accuracy: 0.7714\n",
            "Epoch 2835/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5956 - val_accuracy: 0.7714\n",
            "Epoch 2836/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5958 - val_accuracy: 0.7714\n",
            "Epoch 2837/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5961 - val_accuracy: 0.7714\n",
            "Epoch 2838/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5965 - val_accuracy: 0.7714\n",
            "Epoch 2839/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5969 - val_accuracy: 0.7714\n",
            "Epoch 2840/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5974 - val_accuracy: 0.7714\n",
            "Epoch 2841/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5979 - val_accuracy: 0.7714\n",
            "Epoch 2842/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5983 - val_accuracy: 0.7714\n",
            "Epoch 2843/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5987 - val_accuracy: 0.7714\n",
            "Epoch 2844/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5989 - val_accuracy: 0.7714\n",
            "Epoch 2845/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 1.5991 - val_accuracy: 0.7714\n",
            "Epoch 2846/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.5994 - val_accuracy: 0.7714\n",
            "Epoch 2847/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.5998 - val_accuracy: 0.7714\n",
            "Epoch 2848/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6001 - val_accuracy: 0.7714\n",
            "Epoch 2849/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6006 - val_accuracy: 0.7714\n",
            "Epoch 2850/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6011 - val_accuracy: 0.7714\n",
            "Epoch 2851/4000\n",
            "1/1 [==============================] - 0s 87ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6016 - val_accuracy: 0.7714\n",
            "Epoch 2852/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6022 - val_accuracy: 0.7714\n",
            "Epoch 2853/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6026 - val_accuracy: 0.7714\n",
            "Epoch 2854/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6029 - val_accuracy: 0.7714\n",
            "Epoch 2855/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6032 - val_accuracy: 0.7714\n",
            "Epoch 2856/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6034 - val_accuracy: 0.7714\n",
            "Epoch 2857/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6035 - val_accuracy: 0.7714\n",
            "Epoch 2858/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6038 - val_accuracy: 0.7714\n",
            "Epoch 2859/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6042 - val_accuracy: 0.7714\n",
            "Epoch 2860/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6046 - val_accuracy: 0.7714\n",
            "Epoch 2861/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6050 - val_accuracy: 0.7714\n",
            "Epoch 2862/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6054 - val_accuracy: 0.7714\n",
            "Epoch 2863/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 1.6058 - val_accuracy: 0.7714\n",
            "Epoch 2864/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6062 - val_accuracy: 0.7714\n",
            "Epoch 2865/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6065 - val_accuracy: 0.7714\n",
            "Epoch 2866/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6068 - val_accuracy: 0.7714\n",
            "Epoch 2867/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6071 - val_accuracy: 0.7714\n",
            "Epoch 2868/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6074 - val_accuracy: 0.7714\n",
            "Epoch 2869/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6078 - val_accuracy: 0.7714\n",
            "Epoch 2870/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6082 - val_accuracy: 0.7714\n",
            "Epoch 2871/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6086 - val_accuracy: 0.7714\n",
            "Epoch 2872/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6092 - val_accuracy: 0.7714\n",
            "Epoch 2873/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6096 - val_accuracy: 0.7714\n",
            "Epoch 2874/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6099 - val_accuracy: 0.7714\n",
            "Epoch 2875/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6102 - val_accuracy: 0.7714\n",
            "Epoch 2876/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6103 - val_accuracy: 0.7714\n",
            "Epoch 2877/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6105 - val_accuracy: 0.7714\n",
            "Epoch 2878/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6109 - val_accuracy: 0.7714\n",
            "Epoch 2879/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6112 - val_accuracy: 0.7714\n",
            "Epoch 2880/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6116 - val_accuracy: 0.7714\n",
            "Epoch 2881/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6120 - val_accuracy: 0.7714\n",
            "Epoch 2882/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 1.6125 - val_accuracy: 0.7714\n",
            "Epoch 2883/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6129 - val_accuracy: 0.7714\n",
            "Epoch 2884/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6133 - val_accuracy: 0.7714\n",
            "Epoch 2885/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6137 - val_accuracy: 0.7714\n",
            "Epoch 2886/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6140 - val_accuracy: 0.7714\n",
            "Epoch 2887/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6144 - val_accuracy: 0.7714\n",
            "Epoch 2888/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6148 - val_accuracy: 0.7714\n",
            "Epoch 2889/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6153 - val_accuracy: 0.7714\n",
            "Epoch 2890/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6159 - val_accuracy: 0.7714\n",
            "Epoch 2891/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6164 - val_accuracy: 0.7714\n",
            "Epoch 2892/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6170 - val_accuracy: 0.7714\n",
            "Epoch 2893/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6175 - val_accuracy: 0.7714\n",
            "Epoch 2894/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6179 - val_accuracy: 0.7714\n",
            "Epoch 2895/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6181 - val_accuracy: 0.7714\n",
            "Epoch 2896/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6181 - val_accuracy: 0.7714\n",
            "Epoch 2897/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6182 - val_accuracy: 0.7714\n",
            "Epoch 2898/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6185 - val_accuracy: 0.7714\n",
            "Epoch 2899/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6188 - val_accuracy: 0.7714\n",
            "Epoch 2900/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6192 - val_accuracy: 0.7714\n",
            "Epoch 2901/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 1.6197 - val_accuracy: 0.7714\n",
            "Epoch 2902/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6203 - val_accuracy: 0.7714\n",
            "Epoch 2903/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6208 - val_accuracy: 0.7714\n",
            "Epoch 2904/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6213 - val_accuracy: 0.7714\n",
            "Epoch 2905/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6218 - val_accuracy: 0.7714\n",
            "Epoch 2906/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6221 - val_accuracy: 0.7714\n",
            "Epoch 2907/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6222 - val_accuracy: 0.7714\n",
            "Epoch 2908/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6222 - val_accuracy: 0.7714\n",
            "Epoch 2909/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6223 - val_accuracy: 0.7714\n",
            "Epoch 2910/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6226 - val_accuracy: 0.7714\n",
            "Epoch 2911/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6230 - val_accuracy: 0.7714\n",
            "Epoch 2912/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6235 - val_accuracy: 0.7714\n",
            "Epoch 2913/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6239 - val_accuracy: 0.7714\n",
            "Epoch 2914/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6244 - val_accuracy: 0.7714\n",
            "Epoch 2915/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6249 - val_accuracy: 0.7714\n",
            "Epoch 2916/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6253 - val_accuracy: 0.7714\n",
            "Epoch 2917/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6256 - val_accuracy: 0.7714\n",
            "Epoch 2918/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6259 - val_accuracy: 0.7714\n",
            "Epoch 2919/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6260 - val_accuracy: 0.7714\n",
            "Epoch 2920/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6262 - val_accuracy: 0.7714\n",
            "Epoch 2921/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 1.6266 - val_accuracy: 0.7714\n",
            "Epoch 2922/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6269 - val_accuracy: 0.7714\n",
            "Epoch 2923/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6274 - val_accuracy: 0.7714\n",
            "Epoch 2924/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6280 - val_accuracy: 0.7714\n",
            "Epoch 2925/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6285 - val_accuracy: 0.7714\n",
            "Epoch 2926/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6290 - val_accuracy: 0.7714\n",
            "Epoch 2927/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6293 - val_accuracy: 0.7714\n",
            "Epoch 2928/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6295 - val_accuracy: 0.7714\n",
            "Epoch 2929/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6297 - val_accuracy: 0.7714\n",
            "Epoch 2930/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6300 - val_accuracy: 0.7714\n",
            "Epoch 2931/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6302 - val_accuracy: 0.7714\n",
            "Epoch 2932/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6305 - val_accuracy: 0.7714\n",
            "Epoch 2933/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6309 - val_accuracy: 0.7714\n",
            "Epoch 2934/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6313 - val_accuracy: 0.7714\n",
            "Epoch 2935/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6318 - val_accuracy: 0.7714\n",
            "Epoch 2936/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6323 - val_accuracy: 0.7714\n",
            "Epoch 2937/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6328 - val_accuracy: 0.7714\n",
            "Epoch 2938/4000\n",
            "1/1 [==============================] - 0s 78ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6332 - val_accuracy: 0.7714\n",
            "Epoch 2939/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6334 - val_accuracy: 0.7714\n",
            "Epoch 2940/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6335 - val_accuracy: 0.7714\n",
            "Epoch 2941/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 1.6338 - val_accuracy: 0.7714\n",
            "Epoch 2942/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6342 - val_accuracy: 0.7714\n",
            "Epoch 2943/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6345 - val_accuracy: 0.7714\n",
            "Epoch 2944/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6349 - val_accuracy: 0.7714\n",
            "Epoch 2945/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6354 - val_accuracy: 0.7714\n",
            "Epoch 2946/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6358 - val_accuracy: 0.7714\n",
            "Epoch 2947/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6362 - val_accuracy: 0.7714\n",
            "Epoch 2948/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6365 - val_accuracy: 0.7714\n",
            "Epoch 2949/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6367 - val_accuracy: 0.7714\n",
            "Epoch 2950/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6369 - val_accuracy: 0.7714\n",
            "Epoch 2951/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6371 - val_accuracy: 0.7714\n",
            "Epoch 2952/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6374 - val_accuracy: 0.7714\n",
            "Epoch 2953/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6378 - val_accuracy: 0.7714\n",
            "Epoch 2954/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6382 - val_accuracy: 0.7714\n",
            "Epoch 2955/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6387 - val_accuracy: 0.7714\n",
            "Epoch 2956/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6392 - val_accuracy: 0.7714\n",
            "Epoch 2957/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6398 - val_accuracy: 0.7714\n",
            "Epoch 2958/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6402 - val_accuracy: 0.7714\n",
            "Epoch 2959/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6405 - val_accuracy: 0.7714\n",
            "Epoch 2960/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6407 - val_accuracy: 0.7714\n",
            "Epoch 2961/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6408 - val_accuracy: 0.7714\n",
            "Epoch 2962/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 1.6410 - val_accuracy: 0.7714\n",
            "Epoch 2963/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6413 - val_accuracy: 0.7714\n",
            "Epoch 2964/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6418 - val_accuracy: 0.7714\n",
            "Epoch 2965/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6422 - val_accuracy: 0.7714\n",
            "Epoch 2966/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6427 - val_accuracy: 0.7714\n",
            "Epoch 2967/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6432 - val_accuracy: 0.7714\n",
            "Epoch 2968/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6436 - val_accuracy: 0.7714\n",
            "Epoch 2969/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6439 - val_accuracy: 0.7714\n",
            "Epoch 2970/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6442 - val_accuracy: 0.7714\n",
            "Epoch 2971/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6444 - val_accuracy: 0.7714\n",
            "Epoch 2972/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6445 - val_accuracy: 0.7714\n",
            "Epoch 2973/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6447 - val_accuracy: 0.7714\n",
            "Epoch 2974/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6450 - val_accuracy: 0.7714\n",
            "Epoch 2975/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6453 - val_accuracy: 0.7714\n",
            "Epoch 2976/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6457 - val_accuracy: 0.7714\n",
            "Epoch 2977/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6464 - val_accuracy: 0.7714\n",
            "Epoch 2978/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6471 - val_accuracy: 0.7714\n",
            "Epoch 2979/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6477 - val_accuracy: 0.7714\n",
            "Epoch 2980/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6482 - val_accuracy: 0.7714\n",
            "Epoch 2981/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6486 - val_accuracy: 0.7714\n",
            "Epoch 2982/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6489 - val_accuracy: 0.7714\n",
            "Epoch 2983/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 1.6493 - val_accuracy: 0.7714\n",
            "Epoch 2984/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6496 - val_accuracy: 0.7714\n",
            "Epoch 2985/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6500 - val_accuracy: 0.7714\n",
            "Epoch 2986/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6504 - val_accuracy: 0.7714\n",
            "Epoch 2987/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6507 - val_accuracy: 0.7714\n",
            "Epoch 2988/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6511 - val_accuracy: 0.7714\n",
            "Epoch 2989/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6515 - val_accuracy: 0.7714\n",
            "Epoch 2990/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6519 - val_accuracy: 0.7714\n",
            "Epoch 2991/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6522 - val_accuracy: 0.7714\n",
            "Epoch 2992/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6524 - val_accuracy: 0.7714\n",
            "Epoch 2993/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6526 - val_accuracy: 0.7714\n",
            "Epoch 2994/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6529 - val_accuracy: 0.7714\n",
            "Epoch 2995/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6533 - val_accuracy: 0.7714\n",
            "Epoch 2996/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6538 - val_accuracy: 0.7714\n",
            "Epoch 2997/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6543 - val_accuracy: 0.7714\n",
            "Epoch 2998/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6548 - val_accuracy: 0.7714\n",
            "Epoch 2999/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6553 - val_accuracy: 0.7714\n",
            "Epoch 3000/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6558 - val_accuracy: 0.7714\n",
            "Epoch 3001/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6560 - val_accuracy: 0.7714\n",
            "Epoch 3002/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6562 - val_accuracy: 0.7714\n",
            "Epoch 3003/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6563 - val_accuracy: 0.7714\n",
            "Epoch 3004/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6565 - val_accuracy: 0.7714\n",
            "Epoch 3005/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 1.6568 - val_accuracy: 0.7714\n",
            "Epoch 3006/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6572 - val_accuracy: 0.7714\n",
            "Epoch 3007/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6576 - val_accuracy: 0.7714\n",
            "Epoch 3008/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6580 - val_accuracy: 0.7714\n",
            "Epoch 3009/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6585 - val_accuracy: 0.7714\n",
            "Epoch 3010/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6590 - val_accuracy: 0.7714\n",
            "Epoch 3011/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6593 - val_accuracy: 0.7714\n",
            "Epoch 3012/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6595 - val_accuracy: 0.7714\n",
            "Epoch 3013/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6596 - val_accuracy: 0.7714\n",
            "Epoch 3014/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6597 - val_accuracy: 0.7714\n",
            "Epoch 3015/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6599 - val_accuracy: 0.7714\n",
            "Epoch 3016/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6603 - val_accuracy: 0.7714\n",
            "Epoch 3017/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6608 - val_accuracy: 0.7714\n",
            "Epoch 3018/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6613 - val_accuracy: 0.7714\n",
            "Epoch 3019/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6619 - val_accuracy: 0.7714\n",
            "Epoch 3020/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6624 - val_accuracy: 0.7714\n",
            "Epoch 3021/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6629 - val_accuracy: 0.7714\n",
            "Epoch 3022/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6632 - val_accuracy: 0.7714\n",
            "Epoch 3023/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6634 - val_accuracy: 0.7714\n",
            "Epoch 3024/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6635 - val_accuracy: 0.7714\n",
            "Epoch 3025/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6636 - val_accuracy: 0.7714\n",
            "Epoch 3026/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6638 - val_accuracy: 0.7714\n",
            "Epoch 3027/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6641 - val_accuracy: 0.7714\n",
            "Epoch 3028/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 1.6645 - val_accuracy: 0.7714\n",
            "Epoch 3029/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6651 - val_accuracy: 0.7714\n",
            "Epoch 3030/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6657 - val_accuracy: 0.7714\n",
            "Epoch 3031/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6662 - val_accuracy: 0.7714\n",
            "Epoch 3032/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6667 - val_accuracy: 0.7714\n",
            "Epoch 3033/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6670 - val_accuracy: 0.7714\n",
            "Epoch 3034/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6672 - val_accuracy: 0.7714\n",
            "Epoch 3035/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6673 - val_accuracy: 0.7714\n",
            "Epoch 3036/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6675 - val_accuracy: 0.7714\n",
            "Epoch 3037/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6678 - val_accuracy: 0.7714\n",
            "Epoch 3038/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6680 - val_accuracy: 0.7714\n",
            "Epoch 3039/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6685 - val_accuracy: 0.7714\n",
            "Epoch 3040/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6690 - val_accuracy: 0.7714\n",
            "Epoch 3041/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6695 - val_accuracy: 0.7714\n",
            "Epoch 3042/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6700 - val_accuracy: 0.7714\n",
            "Epoch 3043/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6703 - val_accuracy: 0.7714\n",
            "Epoch 3044/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6706 - val_accuracy: 0.7714\n",
            "Epoch 3045/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6708 - val_accuracy: 0.7714\n",
            "Epoch 3046/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6709 - val_accuracy: 0.7714\n",
            "Epoch 3047/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6712 - val_accuracy: 0.7714\n",
            "Epoch 3048/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6715 - val_accuracy: 0.7714\n",
            "Epoch 3049/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6718 - val_accuracy: 0.7714\n",
            "Epoch 3050/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6723 - val_accuracy: 0.7714\n",
            "Epoch 3051/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6728 - val_accuracy: 0.7714\n",
            "Epoch 3052/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 1.6733 - val_accuracy: 0.7714\n",
            "Epoch 3053/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6737 - val_accuracy: 0.7714\n",
            "Epoch 3054/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6741 - val_accuracy: 0.7714\n",
            "Epoch 3055/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6743 - val_accuracy: 0.7714\n",
            "Epoch 3056/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6744 - val_accuracy: 0.7714\n",
            "Epoch 3057/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6746 - val_accuracy: 0.7714\n",
            "Epoch 3058/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6748 - val_accuracy: 0.7714\n",
            "Epoch 3059/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6750 - val_accuracy: 0.7714\n",
            "Epoch 3060/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6754 - val_accuracy: 0.7714\n",
            "Epoch 3061/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6759 - val_accuracy: 0.7714\n",
            "Epoch 3062/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6766 - val_accuracy: 0.7714\n",
            "Epoch 3063/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6771 - val_accuracy: 0.7714\n",
            "Epoch 3064/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6775 - val_accuracy: 0.7714\n",
            "Epoch 3065/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6777 - val_accuracy: 0.7714\n",
            "Epoch 3066/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6778 - val_accuracy: 0.7714\n",
            "Epoch 3067/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6781 - val_accuracy: 0.7714\n",
            "Epoch 3068/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6783 - val_accuracy: 0.7714\n",
            "Epoch 3069/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6787 - val_accuracy: 0.7714\n",
            "Epoch 3070/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6790 - val_accuracy: 0.7714\n",
            "Epoch 3071/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6794 - val_accuracy: 0.7714\n",
            "Epoch 3072/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6798 - val_accuracy: 0.7714\n",
            "Epoch 3073/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6804 - val_accuracy: 0.7714\n",
            "Epoch 3074/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6808 - val_accuracy: 0.7714\n",
            "Epoch 3075/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6811 - val_accuracy: 0.7714\n",
            "Epoch 3076/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 1.6813 - val_accuracy: 0.7714\n",
            "Epoch 3077/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6814 - val_accuracy: 0.7714\n",
            "Epoch 3078/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6815 - val_accuracy: 0.7714\n",
            "Epoch 3079/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6818 - val_accuracy: 0.7714\n",
            "Epoch 3080/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6822 - val_accuracy: 0.7714\n",
            "Epoch 3081/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6827 - val_accuracy: 0.7714\n",
            "Epoch 3082/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6833 - val_accuracy: 0.7714\n",
            "Epoch 3083/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6839 - val_accuracy: 0.7714\n",
            "Epoch 3084/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6844 - val_accuracy: 0.7714\n",
            "Epoch 3085/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6847 - val_accuracy: 0.7714\n",
            "Epoch 3086/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6849 - val_accuracy: 0.7714\n",
            "Epoch 3087/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6850 - val_accuracy: 0.7714\n",
            "Epoch 3088/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6851 - val_accuracy: 0.7714\n",
            "Epoch 3089/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6853 - val_accuracy: 0.7714\n",
            "Epoch 3090/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6856 - val_accuracy: 0.7714\n",
            "Epoch 3091/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6861 - val_accuracy: 0.7714\n",
            "Epoch 3092/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6865 - val_accuracy: 0.7714\n",
            "Epoch 3093/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6870 - val_accuracy: 0.7714\n",
            "Epoch 3094/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6875 - val_accuracy: 0.7714\n",
            "Epoch 3095/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6880 - val_accuracy: 0.7714\n",
            "Epoch 3096/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6883 - val_accuracy: 0.7714\n",
            "Epoch 3097/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6884 - val_accuracy: 0.7714\n",
            "Epoch 3098/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6886 - val_accuracy: 0.7714\n",
            "Epoch 3099/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6888 - val_accuracy: 0.7714\n",
            "Epoch 3100/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6892 - val_accuracy: 0.7714\n",
            "Epoch 3101/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 1.6895 - val_accuracy: 0.7714\n",
            "Epoch 3102/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6900 - val_accuracy: 0.7714\n",
            "Epoch 3103/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6905 - val_accuracy: 0.7714\n",
            "Epoch 3104/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6910 - val_accuracy: 0.7714\n",
            "Epoch 3105/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6914 - val_accuracy: 0.7714\n",
            "Epoch 3106/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6917 - val_accuracy: 0.7714\n",
            "Epoch 3107/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6919 - val_accuracy: 0.7714\n",
            "Epoch 3108/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6920 - val_accuracy: 0.7714\n",
            "Epoch 3109/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6922 - val_accuracy: 0.7714\n",
            "Epoch 3110/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6925 - val_accuracy: 0.7714\n",
            "Epoch 3111/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6928 - val_accuracy: 0.7714\n",
            "Epoch 3112/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6931 - val_accuracy: 0.7714\n",
            "Epoch 3113/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6935 - val_accuracy: 0.7714\n",
            "Epoch 3114/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6940 - val_accuracy: 0.7571\n",
            "Epoch 3115/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6944 - val_accuracy: 0.7571\n",
            "Epoch 3116/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6947 - val_accuracy: 0.7571\n",
            "Epoch 3117/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6950 - val_accuracy: 0.7571\n",
            "Epoch 3118/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6952 - val_accuracy: 0.7571\n",
            "Epoch 3119/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6954 - val_accuracy: 0.7571\n",
            "Epoch 3120/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6956 - val_accuracy: 0.7571\n",
            "Epoch 3121/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6959 - val_accuracy: 0.7571\n",
            "Epoch 3122/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6963 - val_accuracy: 0.7571\n",
            "Epoch 3123/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6968 - val_accuracy: 0.7571\n",
            "Epoch 3124/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6973 - val_accuracy: 0.7571\n",
            "Epoch 3125/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6978 - val_accuracy: 0.7571\n",
            "Epoch 3126/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6982 - val_accuracy: 0.7571\n",
            "Epoch 3127/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 1.6985 - val_accuracy: 0.7571\n",
            "Epoch 3128/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.6988 - val_accuracy: 0.7571\n",
            "Epoch 3129/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.6990 - val_accuracy: 0.7571\n",
            "Epoch 3130/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.6993 - val_accuracy: 0.7571\n",
            "Epoch 3131/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.6995 - val_accuracy: 0.7571\n",
            "Epoch 3132/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.6998 - val_accuracy: 0.7571\n",
            "Epoch 3133/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7002 - val_accuracy: 0.7571\n",
            "Epoch 3134/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7007 - val_accuracy: 0.7571\n",
            "Epoch 3135/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7011 - val_accuracy: 0.7571\n",
            "Epoch 3136/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7014 - val_accuracy: 0.7571\n",
            "Epoch 3137/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7017 - val_accuracy: 0.7571\n",
            "Epoch 3138/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7020 - val_accuracy: 0.7571\n",
            "Epoch 3139/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7023 - val_accuracy: 0.7571\n",
            "Epoch 3140/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7026 - val_accuracy: 0.7571\n",
            "Epoch 3141/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7029 - val_accuracy: 0.7571\n",
            "Epoch 3142/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7032 - val_accuracy: 0.7571\n",
            "Epoch 3143/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7035 - val_accuracy: 0.7571\n",
            "Epoch 3144/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7040 - val_accuracy: 0.7571\n",
            "Epoch 3145/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7045 - val_accuracy: 0.7571\n",
            "Epoch 3146/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7049 - val_accuracy: 0.7571\n",
            "Epoch 3147/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7052 - val_accuracy: 0.7571\n",
            "Epoch 3148/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7054 - val_accuracy: 0.7571\n",
            "Epoch 3149/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7057 - val_accuracy: 0.7571\n",
            "Epoch 3150/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7059 - val_accuracy: 0.7571\n",
            "Epoch 3151/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7061 - val_accuracy: 0.7571\n",
            "Epoch 3152/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7064 - val_accuracy: 0.7571\n",
            "Epoch 3153/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7067 - val_accuracy: 0.7571\n",
            "Epoch 3154/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 1.7070 - val_accuracy: 0.7571\n",
            "Epoch 3155/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7074 - val_accuracy: 0.7571\n",
            "Epoch 3156/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7079 - val_accuracy: 0.7571\n",
            "Epoch 3157/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7083 - val_accuracy: 0.7571\n",
            "Epoch 3158/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7086 - val_accuracy: 0.7571\n",
            "Epoch 3159/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7090 - val_accuracy: 0.7571\n",
            "Epoch 3160/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7093 - val_accuracy: 0.7571\n",
            "Epoch 3161/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7095 - val_accuracy: 0.7571\n",
            "Epoch 3162/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7098 - val_accuracy: 0.7571\n",
            "Epoch 3163/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7102 - val_accuracy: 0.7571\n",
            "Epoch 3164/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7106 - val_accuracy: 0.7571\n",
            "Epoch 3165/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7110 - val_accuracy: 0.7571\n",
            "Epoch 3166/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7113 - val_accuracy: 0.7571\n",
            "Epoch 3167/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7116 - val_accuracy: 0.7571\n",
            "Epoch 3168/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7119 - val_accuracy: 0.7571\n",
            "Epoch 3169/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7123 - val_accuracy: 0.7571\n",
            "Epoch 3170/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7124 - val_accuracy: 0.7571\n",
            "Epoch 3171/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7127 - val_accuracy: 0.7571\n",
            "Epoch 3172/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7130 - val_accuracy: 0.7571\n",
            "Epoch 3173/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7134 - val_accuracy: 0.7571\n",
            "Epoch 3174/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7139 - val_accuracy: 0.7571\n",
            "Epoch 3175/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7144 - val_accuracy: 0.7571\n",
            "Epoch 3176/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7149 - val_accuracy: 0.7571\n",
            "Epoch 3177/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7154 - val_accuracy: 0.7571\n",
            "Epoch 3178/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7159 - val_accuracy: 0.7571\n",
            "Epoch 3179/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7164 - val_accuracy: 0.7571\n",
            "Epoch 3180/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7167 - val_accuracy: 0.7571\n",
            "Epoch 3181/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7169 - val_accuracy: 0.7571\n",
            "Epoch 3182/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 1.7170 - val_accuracy: 0.7571\n",
            "Epoch 3183/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7172 - val_accuracy: 0.7571\n",
            "Epoch 3184/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7175 - val_accuracy: 0.7571\n",
            "Epoch 3185/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7179 - val_accuracy: 0.7571\n",
            "Epoch 3186/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7184 - val_accuracy: 0.7571\n",
            "Epoch 3187/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7188 - val_accuracy: 0.7571\n",
            "Epoch 3188/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7193 - val_accuracy: 0.7571\n",
            "Epoch 3189/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7196 - val_accuracy: 0.7571\n",
            "Epoch 3190/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7200 - val_accuracy: 0.7571\n",
            "Epoch 3191/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7202 - val_accuracy: 0.7571\n",
            "Epoch 3192/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7205 - val_accuracy: 0.7571\n",
            "Epoch 3193/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7206 - val_accuracy: 0.7571\n",
            "Epoch 3194/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7208 - val_accuracy: 0.7571\n",
            "Epoch 3195/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7210 - val_accuracy: 0.7571\n",
            "Epoch 3196/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7213 - val_accuracy: 0.7571\n",
            "Epoch 3197/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7218 - val_accuracy: 0.7571\n",
            "Epoch 3198/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7223 - val_accuracy: 0.7571\n",
            "Epoch 3199/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7228 - val_accuracy: 0.7571\n",
            "Epoch 3200/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7233 - val_accuracy: 0.7571\n",
            "Epoch 3201/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7236 - val_accuracy: 0.7571\n",
            "Epoch 3202/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7239 - val_accuracy: 0.7571\n",
            "Epoch 3203/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7240 - val_accuracy: 0.7571\n",
            "Epoch 3204/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7243 - val_accuracy: 0.7571\n",
            "Epoch 3205/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7246 - val_accuracy: 0.7571\n",
            "Epoch 3206/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7249 - val_accuracy: 0.7571\n",
            "Epoch 3207/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7253 - val_accuracy: 0.7571\n",
            "Epoch 3208/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7258 - val_accuracy: 0.7571\n",
            "Epoch 3209/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7262 - val_accuracy: 0.7571\n",
            "Epoch 3210/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7266 - val_accuracy: 0.7571\n",
            "Epoch 3211/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 1.7270 - val_accuracy: 0.7571\n",
            "Epoch 3212/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7273 - val_accuracy: 0.7571\n",
            "Epoch 3213/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7275 - val_accuracy: 0.7571\n",
            "Epoch 3214/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7277 - val_accuracy: 0.7571\n",
            "Epoch 3215/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7279 - val_accuracy: 0.7571\n",
            "Epoch 3216/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7282 - val_accuracy: 0.7571\n",
            "Epoch 3217/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7285 - val_accuracy: 0.7571\n",
            "Epoch 3218/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7289 - val_accuracy: 0.7571\n",
            "Epoch 3219/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7293 - val_accuracy: 0.7571\n",
            "Epoch 3220/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7298 - val_accuracy: 0.7571\n",
            "Epoch 3221/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7302 - val_accuracy: 0.7571\n",
            "Epoch 3222/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7306 - val_accuracy: 0.7571\n",
            "Epoch 3223/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7308 - val_accuracy: 0.7571\n",
            "Epoch 3224/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7309 - val_accuracy: 0.7571\n",
            "Epoch 3225/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7311 - val_accuracy: 0.7571\n",
            "Epoch 3226/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7314 - val_accuracy: 0.7571\n",
            "Epoch 3227/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7316 - val_accuracy: 0.7571\n",
            "Epoch 3228/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7320 - val_accuracy: 0.7571\n",
            "Epoch 3229/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7323 - val_accuracy: 0.7571\n",
            "Epoch 3230/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7327 - val_accuracy: 0.7571\n",
            "Epoch 3231/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7331 - val_accuracy: 0.7571\n",
            "Epoch 3232/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7336 - val_accuracy: 0.7571\n",
            "Epoch 3233/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7340 - val_accuracy: 0.7571\n",
            "Epoch 3234/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7342 - val_accuracy: 0.7571\n",
            "Epoch 3235/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7343 - val_accuracy: 0.7571\n",
            "Epoch 3236/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7346 - val_accuracy: 0.7571\n",
            "Epoch 3237/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7348 - val_accuracy: 0.7571\n",
            "Epoch 3238/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7351 - val_accuracy: 0.7571\n",
            "Epoch 3239/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7354 - val_accuracy: 0.7571\n",
            "Epoch 3240/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7358 - val_accuracy: 0.7571\n",
            "Epoch 3241/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 1.7363 - val_accuracy: 0.7571\n",
            "Epoch 3242/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7367 - val_accuracy: 0.7571\n",
            "Epoch 3243/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7372 - val_accuracy: 0.7571\n",
            "Epoch 3244/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7375 - val_accuracy: 0.7571\n",
            "Epoch 3245/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7377 - val_accuracy: 0.7571\n",
            "Epoch 3246/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7379 - val_accuracy: 0.7571\n",
            "Epoch 3247/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7382 - val_accuracy: 0.7571\n",
            "Epoch 3248/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7385 - val_accuracy: 0.7571\n",
            "Epoch 3249/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7389 - val_accuracy: 0.7571\n",
            "Epoch 3250/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7392 - val_accuracy: 0.7571\n",
            "Epoch 3251/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7395 - val_accuracy: 0.7571\n",
            "Epoch 3252/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7400 - val_accuracy: 0.7571\n",
            "Epoch 3253/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7404 - val_accuracy: 0.7571\n",
            "Epoch 3254/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7408 - val_accuracy: 0.7571\n",
            "Epoch 3255/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7412 - val_accuracy: 0.7571\n",
            "Epoch 3256/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7414 - val_accuracy: 0.7571\n",
            "Epoch 3257/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7416 - val_accuracy: 0.7571\n",
            "Epoch 3258/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7417 - val_accuracy: 0.7571\n",
            "Epoch 3259/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7420 - val_accuracy: 0.7571\n",
            "Epoch 3260/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7423 - val_accuracy: 0.7571\n",
            "Epoch 3261/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7427 - val_accuracy: 0.7571\n",
            "Epoch 3262/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7430 - val_accuracy: 0.7571\n",
            "Epoch 3263/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7434 - val_accuracy: 0.7571\n",
            "Epoch 3264/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7437 - val_accuracy: 0.7571\n",
            "Epoch 3265/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7441 - val_accuracy: 0.7571\n",
            "Epoch 3266/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7444 - val_accuracy: 0.7571\n",
            "Epoch 3267/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7447 - val_accuracy: 0.7571\n",
            "Epoch 3268/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7451 - val_accuracy: 0.7571\n",
            "Epoch 3269/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7456 - val_accuracy: 0.7571\n",
            "Epoch 3270/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7460 - val_accuracy: 0.7571\n",
            "Epoch 3271/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7465 - val_accuracy: 0.7571\n",
            "Epoch 3272/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 1.7469 - val_accuracy: 0.7571\n",
            "Epoch 3273/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7473 - val_accuracy: 0.7571\n",
            "Epoch 3274/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7478 - val_accuracy: 0.7571\n",
            "Epoch 3275/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7483 - val_accuracy: 0.7571\n",
            "Epoch 3276/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7486 - val_accuracy: 0.7571\n",
            "Epoch 3277/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7488 - val_accuracy: 0.7571\n",
            "Epoch 3278/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7489 - val_accuracy: 0.7571\n",
            "Epoch 3279/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7491 - val_accuracy: 0.7571\n",
            "Epoch 3280/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7493 - val_accuracy: 0.7571\n",
            "Epoch 3281/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7497 - val_accuracy: 0.7571\n",
            "Epoch 3282/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7500 - val_accuracy: 0.7571\n",
            "Epoch 3283/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7504 - val_accuracy: 0.7571\n",
            "Epoch 3284/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7508 - val_accuracy: 0.7571\n",
            "Epoch 3285/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7513 - val_accuracy: 0.7571\n",
            "Epoch 3286/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7517 - val_accuracy: 0.7571\n",
            "Epoch 3287/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7521 - val_accuracy: 0.7571\n",
            "Epoch 3288/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7525 - val_accuracy: 0.7571\n",
            "Epoch 3289/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7529 - val_accuracy: 0.7571\n",
            "Epoch 3290/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7531 - val_accuracy: 0.7571\n",
            "Epoch 3291/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7533 - val_accuracy: 0.7571\n",
            "Epoch 3292/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7534 - val_accuracy: 0.7571\n",
            "Epoch 3293/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7535 - val_accuracy: 0.7571\n",
            "Epoch 3294/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7538 - val_accuracy: 0.7571\n",
            "Epoch 3295/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7541 - val_accuracy: 0.7571\n",
            "Epoch 3296/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7546 - val_accuracy: 0.7571\n",
            "Epoch 3297/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7551 - val_accuracy: 0.7571\n",
            "Epoch 3298/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7555 - val_accuracy: 0.7571\n",
            "Epoch 3299/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7558 - val_accuracy: 0.7571\n",
            "Epoch 3300/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7562 - val_accuracy: 0.7571\n",
            "Epoch 3301/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7566 - val_accuracy: 0.7571\n",
            "Epoch 3302/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7570 - val_accuracy: 0.7571\n",
            "Epoch 3303/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7572 - val_accuracy: 0.7571\n",
            "Epoch 3304/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 1.7573 - val_accuracy: 0.7571\n",
            "Epoch 3305/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7574 - val_accuracy: 0.7571\n",
            "Epoch 3306/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7577 - val_accuracy: 0.7571\n",
            "Epoch 3307/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7581 - val_accuracy: 0.7571\n",
            "Epoch 3308/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7585 - val_accuracy: 0.7571\n",
            "Epoch 3309/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7589 - val_accuracy: 0.7571\n",
            "Epoch 3310/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7593 - val_accuracy: 0.7571\n",
            "Epoch 3311/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7597 - val_accuracy: 0.7571\n",
            "Epoch 3312/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7600 - val_accuracy: 0.7571\n",
            "Epoch 3313/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7603 - val_accuracy: 0.7571\n",
            "Epoch 3314/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7604 - val_accuracy: 0.7571\n",
            "Epoch 3315/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7606 - val_accuracy: 0.7571\n",
            "Epoch 3316/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7610 - val_accuracy: 0.7571\n",
            "Epoch 3317/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7613 - val_accuracy: 0.7571\n",
            "Epoch 3318/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7617 - val_accuracy: 0.7571\n",
            "Epoch 3319/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7622 - val_accuracy: 0.7571\n",
            "Epoch 3320/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7626 - val_accuracy: 0.7571\n",
            "Epoch 3321/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7630 - val_accuracy: 0.7571\n",
            "Epoch 3322/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7634 - val_accuracy: 0.7571\n",
            "Epoch 3323/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7637 - val_accuracy: 0.7571\n",
            "Epoch 3324/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7638 - val_accuracy: 0.7571\n",
            "Epoch 3325/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7640 - val_accuracy: 0.7571\n",
            "Epoch 3326/4000\n",
            "1/1 [==============================] - 0s 84ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7642 - val_accuracy: 0.7571\n",
            "Epoch 3327/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7645 - val_accuracy: 0.7571\n",
            "Epoch 3328/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7649 - val_accuracy: 0.7571\n",
            "Epoch 3329/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7653 - val_accuracy: 0.7571\n",
            "Epoch 3330/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7658 - val_accuracy: 0.7571\n",
            "Epoch 3331/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7662 - val_accuracy: 0.7571\n",
            "Epoch 3332/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7666 - val_accuracy: 0.7571\n",
            "Epoch 3333/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7668 - val_accuracy: 0.7571\n",
            "Epoch 3334/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7670 - val_accuracy: 0.7571\n",
            "Epoch 3335/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7672 - val_accuracy: 0.7571\n",
            "Epoch 3336/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7673 - val_accuracy: 0.7571\n",
            "Epoch 3337/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7676 - val_accuracy: 0.7571\n",
            "Epoch 3338/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 1.7679 - val_accuracy: 0.7571\n",
            "Epoch 3339/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7683 - val_accuracy: 0.7571\n",
            "Epoch 3340/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7688 - val_accuracy: 0.7571\n",
            "Epoch 3341/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7693 - val_accuracy: 0.7571\n",
            "Epoch 3342/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7697 - val_accuracy: 0.7571\n",
            "Epoch 3343/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7700 - val_accuracy: 0.7571\n",
            "Epoch 3344/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7702 - val_accuracy: 0.7571\n",
            "Epoch 3345/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7703 - val_accuracy: 0.7571\n",
            "Epoch 3346/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7705 - val_accuracy: 0.7571\n",
            "Epoch 3347/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7706 - val_accuracy: 0.7571\n",
            "Epoch 3348/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7710 - val_accuracy: 0.7571\n",
            "Epoch 3349/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7714 - val_accuracy: 0.7571\n",
            "Epoch 3350/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7718 - val_accuracy: 0.7571\n",
            "Epoch 3351/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7722 - val_accuracy: 0.7571\n",
            "Epoch 3352/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7726 - val_accuracy: 0.7571\n",
            "Epoch 3353/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7730 - val_accuracy: 0.7571\n",
            "Epoch 3354/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7733 - val_accuracy: 0.7571\n",
            "Epoch 3355/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7735 - val_accuracy: 0.7571\n",
            "Epoch 3356/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7737 - val_accuracy: 0.7571\n",
            "Epoch 3357/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7739 - val_accuracy: 0.7571\n",
            "Epoch 3358/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7742 - val_accuracy: 0.7571\n",
            "Epoch 3359/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7745 - val_accuracy: 0.7571\n",
            "Epoch 3360/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7749 - val_accuracy: 0.7571\n",
            "Epoch 3361/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7753 - val_accuracy: 0.7571\n",
            "Epoch 3362/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7757 - val_accuracy: 0.7571\n",
            "Epoch 3363/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7760 - val_accuracy: 0.7571\n",
            "Epoch 3364/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7763 - val_accuracy: 0.7571\n",
            "Epoch 3365/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7765 - val_accuracy: 0.7571\n",
            "Epoch 3366/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7767 - val_accuracy: 0.7571\n",
            "Epoch 3367/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7770 - val_accuracy: 0.7571\n",
            "Epoch 3368/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7773 - val_accuracy: 0.7571\n",
            "Epoch 3369/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7776 - val_accuracy: 0.7571\n",
            "Epoch 3370/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7780 - val_accuracy: 0.7571\n",
            "Epoch 3371/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7785 - val_accuracy: 0.7571\n",
            "Epoch 3372/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7789 - val_accuracy: 0.7571\n",
            "Epoch 3373/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7793 - val_accuracy: 0.7571\n",
            "Epoch 3374/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 1.7796 - val_accuracy: 0.7571\n",
            "Epoch 3375/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7798 - val_accuracy: 0.7571\n",
            "Epoch 3376/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7800 - val_accuracy: 0.7571\n",
            "Epoch 3377/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7801 - val_accuracy: 0.7571\n",
            "Epoch 3378/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7804 - val_accuracy: 0.7571\n",
            "Epoch 3379/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7807 - val_accuracy: 0.7571\n",
            "Epoch 3380/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7811 - val_accuracy: 0.7571\n",
            "Epoch 3381/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7815 - val_accuracy: 0.7571\n",
            "Epoch 3382/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7819 - val_accuracy: 0.7571\n",
            "Epoch 3383/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7823 - val_accuracy: 0.7571\n",
            "Epoch 3384/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7826 - val_accuracy: 0.7571\n",
            "Epoch 3385/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7829 - val_accuracy: 0.7571\n",
            "Epoch 3386/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7831 - val_accuracy: 0.7571\n",
            "Epoch 3387/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7833 - val_accuracy: 0.7571\n",
            "Epoch 3388/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7834 - val_accuracy: 0.7571\n",
            "Epoch 3389/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7837 - val_accuracy: 0.7571\n",
            "Epoch 3390/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7840 - val_accuracy: 0.7571\n",
            "Epoch 3391/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7844 - val_accuracy: 0.7571\n",
            "Epoch 3392/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7849 - val_accuracy: 0.7571\n",
            "Epoch 3393/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7853 - val_accuracy: 0.7571\n",
            "Epoch 3394/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7856 - val_accuracy: 0.7571\n",
            "Epoch 3395/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7860 - val_accuracy: 0.7571\n",
            "Epoch 3396/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7863 - val_accuracy: 0.7571\n",
            "Epoch 3397/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7865 - val_accuracy: 0.7571\n",
            "Epoch 3398/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7866 - val_accuracy: 0.7571\n",
            "Epoch 3399/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7868 - val_accuracy: 0.7571\n",
            "Epoch 3400/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7871 - val_accuracy: 0.7571\n",
            "Epoch 3401/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7875 - val_accuracy: 0.7571\n",
            "Epoch 3402/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7880 - val_accuracy: 0.7571\n",
            "Epoch 3403/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7884 - val_accuracy: 0.7571\n",
            "Epoch 3404/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7889 - val_accuracy: 0.7571\n",
            "Epoch 3405/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7892 - val_accuracy: 0.7571\n",
            "Epoch 3406/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7895 - val_accuracy: 0.7571\n",
            "Epoch 3407/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7896 - val_accuracy: 0.7571\n",
            "Epoch 3408/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7898 - val_accuracy: 0.7571\n",
            "Epoch 3409/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7899 - val_accuracy: 0.7571\n",
            "Epoch 3410/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 1.7902 - val_accuracy: 0.7571\n",
            "Epoch 3411/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7907 - val_accuracy: 0.7571\n",
            "Epoch 3412/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7912 - val_accuracy: 0.7571\n",
            "Epoch 3413/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7917 - val_accuracy: 0.7571\n",
            "Epoch 3414/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7921 - val_accuracy: 0.7571\n",
            "Epoch 3415/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7924 - val_accuracy: 0.7571\n",
            "Epoch 3416/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7927 - val_accuracy: 0.7571\n",
            "Epoch 3417/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7929 - val_accuracy: 0.7571\n",
            "Epoch 3418/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7930 - val_accuracy: 0.7571\n",
            "Epoch 3419/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7931 - val_accuracy: 0.7571\n",
            "Epoch 3420/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7933 - val_accuracy: 0.7571\n",
            "Epoch 3421/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7937 - val_accuracy: 0.7571\n",
            "Epoch 3422/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7941 - val_accuracy: 0.7571\n",
            "Epoch 3423/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7945 - val_accuracy: 0.7571\n",
            "Epoch 3424/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7949 - val_accuracy: 0.7571\n",
            "Epoch 3425/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7953 - val_accuracy: 0.7571\n",
            "Epoch 3426/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7957 - val_accuracy: 0.7571\n",
            "Epoch 3427/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7960 - val_accuracy: 0.7571\n",
            "Epoch 3428/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7961 - val_accuracy: 0.7571\n",
            "Epoch 3429/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7962 - val_accuracy: 0.7571\n",
            "Epoch 3430/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7963 - val_accuracy: 0.7571\n",
            "Epoch 3431/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7965 - val_accuracy: 0.7571\n",
            "Epoch 3432/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7969 - val_accuracy: 0.7571\n",
            "Epoch 3433/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7974 - val_accuracy: 0.7571\n",
            "Epoch 3434/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7979 - val_accuracy: 0.7571\n",
            "Epoch 3435/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7983 - val_accuracy: 0.7571\n",
            "Epoch 3436/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7986 - val_accuracy: 0.7571\n",
            "Epoch 3437/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7990 - val_accuracy: 0.7571\n",
            "Epoch 3438/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7992 - val_accuracy: 0.7571\n",
            "Epoch 3439/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7992 - val_accuracy: 0.7571\n",
            "Epoch 3440/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7994 - val_accuracy: 0.7571\n",
            "Epoch 3441/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.7997 - val_accuracy: 0.7571\n",
            "Epoch 3442/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8002 - val_accuracy: 0.7571\n",
            "Epoch 3443/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8007 - val_accuracy: 0.7571\n",
            "Epoch 3444/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8013 - val_accuracy: 0.7571\n",
            "Epoch 3445/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8018 - val_accuracy: 0.7571\n",
            "Epoch 3446/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8023 - val_accuracy: 0.7571\n",
            "Epoch 3447/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8027 - val_accuracy: 0.7571\n",
            "Epoch 3448/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8031 - val_accuracy: 0.7571\n",
            "Epoch 3449/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 1.8032 - val_accuracy: 0.7571\n",
            "Epoch 3450/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8033 - val_accuracy: 0.7571\n",
            "Epoch 3451/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8034 - val_accuracy: 0.7571\n",
            "Epoch 3452/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8037 - val_accuracy: 0.7571\n",
            "Epoch 3453/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8040 - val_accuracy: 0.7571\n",
            "Epoch 3454/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8045 - val_accuracy: 0.7571\n",
            "Epoch 3455/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8049 - val_accuracy: 0.7571\n",
            "Epoch 3456/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8053 - val_accuracy: 0.7571\n",
            "Epoch 3457/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8056 - val_accuracy: 0.7571\n",
            "Epoch 3458/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8060 - val_accuracy: 0.7571\n",
            "Epoch 3459/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8062 - val_accuracy: 0.7571\n",
            "Epoch 3460/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8063 - val_accuracy: 0.7571\n",
            "Epoch 3461/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8066 - val_accuracy: 0.7571\n",
            "Epoch 3462/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8069 - val_accuracy: 0.7571\n",
            "Epoch 3463/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8073 - val_accuracy: 0.7571\n",
            "Epoch 3464/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8077 - val_accuracy: 0.7571\n",
            "Epoch 3465/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8081 - val_accuracy: 0.7571\n",
            "Epoch 3466/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8084 - val_accuracy: 0.7571\n",
            "Epoch 3467/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8087 - val_accuracy: 0.7571\n",
            "Epoch 3468/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8088 - val_accuracy: 0.7571\n",
            "Epoch 3469/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8090 - val_accuracy: 0.7571\n",
            "Epoch 3470/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8091 - val_accuracy: 0.7571\n",
            "Epoch 3471/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8093 - val_accuracy: 0.7571\n",
            "Epoch 3472/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8096 - val_accuracy: 0.7571\n",
            "Epoch 3473/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8101 - val_accuracy: 0.7571\n",
            "Epoch 3474/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8106 - val_accuracy: 0.7571\n",
            "Epoch 3475/4000\n",
            "1/1 [==============================] - 0s 84ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8111 - val_accuracy: 0.7571\n",
            "Epoch 3476/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8114 - val_accuracy: 0.7571\n",
            "Epoch 3477/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8117 - val_accuracy: 0.7571\n",
            "Epoch 3478/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8120 - val_accuracy: 0.7571\n",
            "Epoch 3479/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8122 - val_accuracy: 0.7571\n",
            "Epoch 3480/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8123 - val_accuracy: 0.7571\n",
            "Epoch 3481/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8124 - val_accuracy: 0.7571\n",
            "Epoch 3482/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8126 - val_accuracy: 0.7571\n",
            "Epoch 3483/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8129 - val_accuracy: 0.7571\n",
            "Epoch 3484/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8134 - val_accuracy: 0.7571\n",
            "Epoch 3485/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8140 - val_accuracy: 0.7571\n",
            "Epoch 3486/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8145 - val_accuracy: 0.7571\n",
            "Epoch 3487/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8149 - val_accuracy: 0.7571\n",
            "Epoch 3488/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8152 - val_accuracy: 0.7571\n",
            "Epoch 3489/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8154 - val_accuracy: 0.7571\n",
            "Epoch 3490/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 1.8156 - val_accuracy: 0.7571\n",
            "Epoch 3491/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8157 - val_accuracy: 0.7571\n",
            "Epoch 3492/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8159 - val_accuracy: 0.7571\n",
            "Epoch 3493/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8162 - val_accuracy: 0.7571\n",
            "Epoch 3494/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8166 - val_accuracy: 0.7571\n",
            "Epoch 3495/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8170 - val_accuracy: 0.7571\n",
            "Epoch 3496/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8176 - val_accuracy: 0.7571\n",
            "Epoch 3497/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8179 - val_accuracy: 0.7571\n",
            "Epoch 3498/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8181 - val_accuracy: 0.7571\n",
            "Epoch 3499/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8184 - val_accuracy: 0.7571\n",
            "Epoch 3500/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8186 - val_accuracy: 0.7571\n",
            "Epoch 3501/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8187 - val_accuracy: 0.7571\n",
            "Epoch 3502/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8188 - val_accuracy: 0.7571\n",
            "Epoch 3503/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8191 - val_accuracy: 0.7571\n",
            "Epoch 3504/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8194 - val_accuracy: 0.7571\n",
            "Epoch 3505/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8199 - val_accuracy: 0.7571\n",
            "Epoch 3506/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8204 - val_accuracy: 0.7571\n",
            "Epoch 3507/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8208 - val_accuracy: 0.7571\n",
            "Epoch 3508/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8212 - val_accuracy: 0.7571\n",
            "Epoch 3509/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8214 - val_accuracy: 0.7571\n",
            "Epoch 3510/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8216 - val_accuracy: 0.7571\n",
            "Epoch 3511/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8218 - val_accuracy: 0.7571\n",
            "Epoch 3512/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8219 - val_accuracy: 0.7571\n",
            "Epoch 3513/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8221 - val_accuracy: 0.7571\n",
            "Epoch 3514/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8223 - val_accuracy: 0.7571\n",
            "Epoch 3515/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8227 - val_accuracy: 0.7571\n",
            "Epoch 3516/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8231 - val_accuracy: 0.7571\n",
            "Epoch 3517/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8236 - val_accuracy: 0.7571\n",
            "Epoch 3518/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8239 - val_accuracy: 0.7571\n",
            "Epoch 3519/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8242 - val_accuracy: 0.7571\n",
            "Epoch 3520/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8245 - val_accuracy: 0.7571\n",
            "Epoch 3521/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8247 - val_accuracy: 0.7571\n",
            "Epoch 3522/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8248 - val_accuracy: 0.7571\n",
            "Epoch 3523/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8250 - val_accuracy: 0.7571\n",
            "Epoch 3524/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8253 - val_accuracy: 0.7571\n",
            "Epoch 3525/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8256 - val_accuracy: 0.7571\n",
            "Epoch 3526/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8261 - val_accuracy: 0.7571\n",
            "Epoch 3527/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8266 - val_accuracy: 0.7571\n",
            "Epoch 3528/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8270 - val_accuracy: 0.7571\n",
            "Epoch 3529/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8274 - val_accuracy: 0.7571\n",
            "Epoch 3530/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8277 - val_accuracy: 0.7571\n",
            "Epoch 3531/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8278 - val_accuracy: 0.7571\n",
            "Epoch 3532/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 1.8279 - val_accuracy: 0.7571\n",
            "Epoch 3533/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8280 - val_accuracy: 0.7571\n",
            "Epoch 3534/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8283 - val_accuracy: 0.7571\n",
            "Epoch 3535/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8287 - val_accuracy: 0.7571\n",
            "Epoch 3536/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8292 - val_accuracy: 0.7571\n",
            "Epoch 3537/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8297 - val_accuracy: 0.7571\n",
            "Epoch 3538/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8303 - val_accuracy: 0.7571\n",
            "Epoch 3539/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8309 - val_accuracy: 0.7571\n",
            "Epoch 3540/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8314 - val_accuracy: 0.7571\n",
            "Epoch 3541/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8317 - val_accuracy: 0.7571\n",
            "Epoch 3542/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8319 - val_accuracy: 0.7571\n",
            "Epoch 3543/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8321 - val_accuracy: 0.7571\n",
            "Epoch 3544/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8323 - val_accuracy: 0.7571\n",
            "Epoch 3545/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8326 - val_accuracy: 0.7571\n",
            "Epoch 3546/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8328 - val_accuracy: 0.7571\n",
            "Epoch 3547/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8330 - val_accuracy: 0.7571\n",
            "Epoch 3548/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8333 - val_accuracy: 0.7571\n",
            "Epoch 3549/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8336 - val_accuracy: 0.7571\n",
            "Epoch 3550/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8341 - val_accuracy: 0.7571\n",
            "Epoch 3551/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8345 - val_accuracy: 0.7571\n",
            "Epoch 3552/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8348 - val_accuracy: 0.7571\n",
            "Epoch 3553/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8350 - val_accuracy: 0.7571\n",
            "Epoch 3554/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8352 - val_accuracy: 0.7571\n",
            "Epoch 3555/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8355 - val_accuracy: 0.7571\n",
            "Epoch 3556/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8358 - val_accuracy: 0.7571\n",
            "Epoch 3557/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8361 - val_accuracy: 0.7571\n",
            "Epoch 3558/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8364 - val_accuracy: 0.7571\n",
            "Epoch 3559/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8367 - val_accuracy: 0.7571\n",
            "Epoch 3560/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8369 - val_accuracy: 0.7571\n",
            "Epoch 3561/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8371 - val_accuracy: 0.7571\n",
            "Epoch 3562/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8374 - val_accuracy: 0.7571\n",
            "Epoch 3563/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8377 - val_accuracy: 0.7571\n",
            "Epoch 3564/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8381 - val_accuracy: 0.7571\n",
            "Epoch 3565/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8385 - val_accuracy: 0.7571\n",
            "Epoch 3566/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8389 - val_accuracy: 0.7571\n",
            "Epoch 3567/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8393 - val_accuracy: 0.7571\n",
            "Epoch 3568/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8396 - val_accuracy: 0.7571\n",
            "Epoch 3569/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8399 - val_accuracy: 0.7571\n",
            "Epoch 3570/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8401 - val_accuracy: 0.7571\n",
            "Epoch 3571/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8403 - val_accuracy: 0.7571\n",
            "Epoch 3572/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8406 - val_accuracy: 0.7571\n",
            "Epoch 3573/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8408 - val_accuracy: 0.7571\n",
            "Epoch 3574/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8410 - val_accuracy: 0.7571\n",
            "Epoch 3575/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8413 - val_accuracy: 0.7571\n",
            "Epoch 3576/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8416 - val_accuracy: 0.7571\n",
            "Epoch 3577/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 1.8420 - val_accuracy: 0.7571\n",
            "Epoch 3578/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8424 - val_accuracy: 0.7571\n",
            "Epoch 3579/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8427 - val_accuracy: 0.7571\n",
            "Epoch 3580/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8431 - val_accuracy: 0.7571\n",
            "Epoch 3581/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8433 - val_accuracy: 0.7571\n",
            "Epoch 3582/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8435 - val_accuracy: 0.7571\n",
            "Epoch 3583/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8437 - val_accuracy: 0.7571\n",
            "Epoch 3584/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8440 - val_accuracy: 0.7571\n",
            "Epoch 3585/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8444 - val_accuracy: 0.7571\n",
            "Epoch 3586/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8447 - val_accuracy: 0.7571\n",
            "Epoch 3587/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8451 - val_accuracy: 0.7571\n",
            "Epoch 3588/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8454 - val_accuracy: 0.7571\n",
            "Epoch 3589/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8457 - val_accuracy: 0.7571\n",
            "Epoch 3590/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8459 - val_accuracy: 0.7571\n",
            "Epoch 3591/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8461 - val_accuracy: 0.7571\n",
            "Epoch 3592/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8462 - val_accuracy: 0.7571\n",
            "Epoch 3593/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8464 - val_accuracy: 0.7571\n",
            "Epoch 3594/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8467 - val_accuracy: 0.7571\n",
            "Epoch 3595/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8470 - val_accuracy: 0.7571\n",
            "Epoch 3596/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8473 - val_accuracy: 0.7571\n",
            "Epoch 3597/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8477 - val_accuracy: 0.7571\n",
            "Epoch 3598/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8481 - val_accuracy: 0.7571\n",
            "Epoch 3599/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8485 - val_accuracy: 0.7571\n",
            "Epoch 3600/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8488 - val_accuracy: 0.7571\n",
            "Epoch 3601/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8491 - val_accuracy: 0.7571\n",
            "Epoch 3602/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8493 - val_accuracy: 0.7571\n",
            "Epoch 3603/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8495 - val_accuracy: 0.7571\n",
            "Epoch 3604/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8497 - val_accuracy: 0.7571\n",
            "Epoch 3605/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8500 - val_accuracy: 0.7571\n",
            "Epoch 3606/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8503 - val_accuracy: 0.7571\n",
            "Epoch 3607/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8507 - val_accuracy: 0.7571\n",
            "Epoch 3608/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8510 - val_accuracy: 0.7571\n",
            "Epoch 3609/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8514 - val_accuracy: 0.7571\n",
            "Epoch 3610/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8517 - val_accuracy: 0.7571\n",
            "Epoch 3611/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8519 - val_accuracy: 0.7571\n",
            "Epoch 3612/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8522 - val_accuracy: 0.7571\n",
            "Epoch 3613/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8524 - val_accuracy: 0.7571\n",
            "Epoch 3614/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8526 - val_accuracy: 0.7571\n",
            "Epoch 3615/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8529 - val_accuracy: 0.7571\n",
            "Epoch 3616/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8532 - val_accuracy: 0.7571\n",
            "Epoch 3617/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8536 - val_accuracy: 0.7571\n",
            "Epoch 3618/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8540 - val_accuracy: 0.7571\n",
            "Epoch 3619/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8543 - val_accuracy: 0.7571\n",
            "Epoch 3620/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8547 - val_accuracy: 0.7571\n",
            "Epoch 3621/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8549 - val_accuracy: 0.7571\n",
            "Epoch 3622/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8552 - val_accuracy: 0.7571\n",
            "Epoch 3623/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8554 - val_accuracy: 0.7571\n",
            "Epoch 3624/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0023 - accuracy: 1.0000 - val_loss: 1.8556 - val_accuracy: 0.7571\n",
            "Epoch 3625/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8559 - val_accuracy: 0.7571\n",
            "Epoch 3626/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8562 - val_accuracy: 0.7571\n",
            "Epoch 3627/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8565 - val_accuracy: 0.7571\n",
            "Epoch 3628/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8568 - val_accuracy: 0.7571\n",
            "Epoch 3629/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8572 - val_accuracy: 0.7571\n",
            "Epoch 3630/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8575 - val_accuracy: 0.7571\n",
            "Epoch 3631/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8578 - val_accuracy: 0.7571\n",
            "Epoch 3632/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8582 - val_accuracy: 0.7571\n",
            "Epoch 3633/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8584 - val_accuracy: 0.7571\n",
            "Epoch 3634/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8586 - val_accuracy: 0.7571\n",
            "Epoch 3635/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8588 - val_accuracy: 0.7571\n",
            "Epoch 3636/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8591 - val_accuracy: 0.7571\n",
            "Epoch 3637/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8594 - val_accuracy: 0.7571\n",
            "Epoch 3638/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8597 - val_accuracy: 0.7571\n",
            "Epoch 3639/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8600 - val_accuracy: 0.7571\n",
            "Epoch 3640/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8603 - val_accuracy: 0.7571\n",
            "Epoch 3641/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8606 - val_accuracy: 0.7571\n",
            "Epoch 3642/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8609 - val_accuracy: 0.7571\n",
            "Epoch 3643/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8611 - val_accuracy: 0.7571\n",
            "Epoch 3644/4000\n",
            "1/1 [==============================] - 0s 220ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8614 - val_accuracy: 0.7571\n",
            "Epoch 3645/4000\n",
            "1/1 [==============================] - 0s 267ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8616 - val_accuracy: 0.7571\n",
            "Epoch 3646/4000\n",
            "1/1 [==============================] - 0s 166ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8619 - val_accuracy: 0.7571\n",
            "Epoch 3647/4000\n",
            "1/1 [==============================] - 0s 119ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8623 - val_accuracy: 0.7571\n",
            "Epoch 3648/4000\n",
            "1/1 [==============================] - 0s 166ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8626 - val_accuracy: 0.7571\n",
            "Epoch 3649/4000\n",
            "1/1 [==============================] - 0s 121ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8629 - val_accuracy: 0.7571\n",
            "Epoch 3650/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8632 - val_accuracy: 0.7571\n",
            "Epoch 3651/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8636 - val_accuracy: 0.7571\n",
            "Epoch 3652/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8639 - val_accuracy: 0.7571\n",
            "Epoch 3653/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8642 - val_accuracy: 0.7571\n",
            "Epoch 3654/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8644 - val_accuracy: 0.7571\n",
            "Epoch 3655/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8645 - val_accuracy: 0.7571\n",
            "Epoch 3656/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8647 - val_accuracy: 0.7571\n",
            "Epoch 3657/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8649 - val_accuracy: 0.7571\n",
            "Epoch 3658/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8652 - val_accuracy: 0.7571\n",
            "Epoch 3659/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8655 - val_accuracy: 0.7571\n",
            "Epoch 3660/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8658 - val_accuracy: 0.7571\n",
            "Epoch 3661/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8661 - val_accuracy: 0.7571\n",
            "Epoch 3662/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8665 - val_accuracy: 0.7571\n",
            "Epoch 3663/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8669 - val_accuracy: 0.7571\n",
            "Epoch 3664/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8672 - val_accuracy: 0.7571\n",
            "Epoch 3665/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8675 - val_accuracy: 0.7571\n",
            "Epoch 3666/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8677 - val_accuracy: 0.7571\n",
            "Epoch 3667/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8679 - val_accuracy: 0.7571\n",
            "Epoch 3668/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8681 - val_accuracy: 0.7571\n",
            "Epoch 3669/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8684 - val_accuracy: 0.7571\n",
            "Epoch 3670/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8687 - val_accuracy: 0.7571\n",
            "Epoch 3671/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8690 - val_accuracy: 0.7571\n",
            "Epoch 3672/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8693 - val_accuracy: 0.7571\n",
            "Epoch 3673/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 1.8697 - val_accuracy: 0.7571\n",
            "Epoch 3674/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8700 - val_accuracy: 0.7571\n",
            "Epoch 3675/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8703 - val_accuracy: 0.7571\n",
            "Epoch 3676/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8705 - val_accuracy: 0.7571\n",
            "Epoch 3677/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8707 - val_accuracy: 0.7571\n",
            "Epoch 3678/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8710 - val_accuracy: 0.7571\n",
            "Epoch 3679/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8712 - val_accuracy: 0.7571\n",
            "Epoch 3680/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8715 - val_accuracy: 0.7571\n",
            "Epoch 3681/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8718 - val_accuracy: 0.7571\n",
            "Epoch 3682/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8722 - val_accuracy: 0.7571\n",
            "Epoch 3683/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8725 - val_accuracy: 0.7571\n",
            "Epoch 3684/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8728 - val_accuracy: 0.7571\n",
            "Epoch 3685/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8730 - val_accuracy: 0.7571\n",
            "Epoch 3686/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8732 - val_accuracy: 0.7571\n",
            "Epoch 3687/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8735 - val_accuracy: 0.7571\n",
            "Epoch 3688/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8738 - val_accuracy: 0.7571\n",
            "Epoch 3689/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8741 - val_accuracy: 0.7571\n",
            "Epoch 3690/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8743 - val_accuracy: 0.7571\n",
            "Epoch 3691/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8745 - val_accuracy: 0.7571\n",
            "Epoch 3692/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8747 - val_accuracy: 0.7571\n",
            "Epoch 3693/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8752 - val_accuracy: 0.7571\n",
            "Epoch 3694/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8756 - val_accuracy: 0.7571\n",
            "Epoch 3695/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8760 - val_accuracy: 0.7571\n",
            "Epoch 3696/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8764 - val_accuracy: 0.7571\n",
            "Epoch 3697/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8768 - val_accuracy: 0.7571\n",
            "Epoch 3698/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8772 - val_accuracy: 0.7571\n",
            "Epoch 3699/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8776 - val_accuracy: 0.7571\n",
            "Epoch 3700/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8780 - val_accuracy: 0.7571\n",
            "Epoch 3701/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8782 - val_accuracy: 0.7571\n",
            "Epoch 3702/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8785 - val_accuracy: 0.7571\n",
            "Epoch 3703/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8788 - val_accuracy: 0.7571\n",
            "Epoch 3704/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8790 - val_accuracy: 0.7571\n",
            "Epoch 3705/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8792 - val_accuracy: 0.7571\n",
            "Epoch 3706/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8794 - val_accuracy: 0.7571\n",
            "Epoch 3707/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8797 - val_accuracy: 0.7571\n",
            "Epoch 3708/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8801 - val_accuracy: 0.7571\n",
            "Epoch 3709/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8805 - val_accuracy: 0.7571\n",
            "Epoch 3710/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8808 - val_accuracy: 0.7571\n",
            "Epoch 3711/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8810 - val_accuracy: 0.7571\n",
            "Epoch 3712/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8812 - val_accuracy: 0.7571\n",
            "Epoch 3713/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8816 - val_accuracy: 0.7571\n",
            "Epoch 3714/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8819 - val_accuracy: 0.7571\n",
            "Epoch 3715/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8822 - val_accuracy: 0.7571\n",
            "Epoch 3716/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8824 - val_accuracy: 0.7571\n",
            "Epoch 3717/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8826 - val_accuracy: 0.7571\n",
            "Epoch 3718/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8828 - val_accuracy: 0.7571\n",
            "Epoch 3719/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8831 - val_accuracy: 0.7571\n",
            "Epoch 3720/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8835 - val_accuracy: 0.7571\n",
            "Epoch 3721/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8837 - val_accuracy: 0.7571\n",
            "Epoch 3722/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8840 - val_accuracy: 0.7571\n",
            "Epoch 3723/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8843 - val_accuracy: 0.7571\n",
            "Epoch 3724/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8847 - val_accuracy: 0.7571\n",
            "Epoch 3725/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8850 - val_accuracy: 0.7571\n",
            "Epoch 3726/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0021 - accuracy: 1.0000 - val_loss: 1.8852 - val_accuracy: 0.7571\n",
            "Epoch 3727/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8855 - val_accuracy: 0.7571\n",
            "Epoch 3728/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8858 - val_accuracy: 0.7571\n",
            "Epoch 3729/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8861 - val_accuracy: 0.7571\n",
            "Epoch 3730/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8864 - val_accuracy: 0.7571\n",
            "Epoch 3731/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8867 - val_accuracy: 0.7571\n",
            "Epoch 3732/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8869 - val_accuracy: 0.7571\n",
            "Epoch 3733/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8871 - val_accuracy: 0.7571\n",
            "Epoch 3734/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8873 - val_accuracy: 0.7571\n",
            "Epoch 3735/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8874 - val_accuracy: 0.7571\n",
            "Epoch 3736/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8876 - val_accuracy: 0.7571\n",
            "Epoch 3737/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8879 - val_accuracy: 0.7571\n",
            "Epoch 3738/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8882 - val_accuracy: 0.7571\n",
            "Epoch 3739/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8886 - val_accuracy: 0.7571\n",
            "Epoch 3740/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8890 - val_accuracy: 0.7571\n",
            "Epoch 3741/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8894 - val_accuracy: 0.7571\n",
            "Epoch 3742/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8897 - val_accuracy: 0.7571\n",
            "Epoch 3743/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8900 - val_accuracy: 0.7571\n",
            "Epoch 3744/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8902 - val_accuracy: 0.7571\n",
            "Epoch 3745/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8905 - val_accuracy: 0.7571\n",
            "Epoch 3746/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8907 - val_accuracy: 0.7571\n",
            "Epoch 3747/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8908 - val_accuracy: 0.7571\n",
            "Epoch 3748/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8910 - val_accuracy: 0.7571\n",
            "Epoch 3749/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8914 - val_accuracy: 0.7571\n",
            "Epoch 3750/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8918 - val_accuracy: 0.7571\n",
            "Epoch 3751/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8921 - val_accuracy: 0.7571\n",
            "Epoch 3752/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8924 - val_accuracy: 0.7571\n",
            "Epoch 3753/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8927 - val_accuracy: 0.7571\n",
            "Epoch 3754/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8929 - val_accuracy: 0.7571\n",
            "Epoch 3755/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8931 - val_accuracy: 0.7571\n",
            "Epoch 3756/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8933 - val_accuracy: 0.7571\n",
            "Epoch 3757/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8935 - val_accuracy: 0.7571\n",
            "Epoch 3758/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8938 - val_accuracy: 0.7571\n",
            "Epoch 3759/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8941 - val_accuracy: 0.7571\n",
            "Epoch 3760/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8945 - val_accuracy: 0.7571\n",
            "Epoch 3761/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8948 - val_accuracy: 0.7571\n",
            "Epoch 3762/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8952 - val_accuracy: 0.7571\n",
            "Epoch 3763/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8955 - val_accuracy: 0.7571\n",
            "Epoch 3764/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8956 - val_accuracy: 0.7571\n",
            "Epoch 3765/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8958 - val_accuracy: 0.7571\n",
            "Epoch 3766/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8960 - val_accuracy: 0.7571\n",
            "Epoch 3767/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8963 - val_accuracy: 0.7571\n",
            "Epoch 3768/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8965 - val_accuracy: 0.7571\n",
            "Epoch 3769/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8968 - val_accuracy: 0.7571\n",
            "Epoch 3770/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8972 - val_accuracy: 0.7571\n",
            "Epoch 3771/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8976 - val_accuracy: 0.7571\n",
            "Epoch 3772/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8981 - val_accuracy: 0.7571\n",
            "Epoch 3773/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8985 - val_accuracy: 0.7571\n",
            "Epoch 3774/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8988 - val_accuracy: 0.7571\n",
            "Epoch 3775/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8990 - val_accuracy: 0.7571\n",
            "Epoch 3776/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8991 - val_accuracy: 0.7571\n",
            "Epoch 3777/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8992 - val_accuracy: 0.7571\n",
            "Epoch 3778/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8993 - val_accuracy: 0.7571\n",
            "Epoch 3779/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8995 - val_accuracy: 0.7571\n",
            "Epoch 3780/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.8998 - val_accuracy: 0.7571\n",
            "Epoch 3781/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0020 - accuracy: 1.0000 - val_loss: 1.9001 - val_accuracy: 0.7571\n",
            "Epoch 3782/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9004 - val_accuracy: 0.7571\n",
            "Epoch 3783/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9007 - val_accuracy: 0.7571\n",
            "Epoch 3784/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9010 - val_accuracy: 0.7571\n",
            "Epoch 3785/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9014 - val_accuracy: 0.7571\n",
            "Epoch 3786/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9017 - val_accuracy: 0.7571\n",
            "Epoch 3787/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9021 - val_accuracy: 0.7571\n",
            "Epoch 3788/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9025 - val_accuracy: 0.7571\n",
            "Epoch 3789/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9028 - val_accuracy: 0.7571\n",
            "Epoch 3790/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9032 - val_accuracy: 0.7571\n",
            "Epoch 3791/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9036 - val_accuracy: 0.7571\n",
            "Epoch 3792/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9040 - val_accuracy: 0.7571\n",
            "Epoch 3793/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9043 - val_accuracy: 0.7571\n",
            "Epoch 3794/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9047 - val_accuracy: 0.7571\n",
            "Epoch 3795/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9050 - val_accuracy: 0.7571\n",
            "Epoch 3796/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9052 - val_accuracy: 0.7571\n",
            "Epoch 3797/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9053 - val_accuracy: 0.7571\n",
            "Epoch 3798/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9054 - val_accuracy: 0.7571\n",
            "Epoch 3799/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9056 - val_accuracy: 0.7571\n",
            "Epoch 3800/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9058 - val_accuracy: 0.7571\n",
            "Epoch 3801/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9062 - val_accuracy: 0.7571\n",
            "Epoch 3802/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9066 - val_accuracy: 0.7571\n",
            "Epoch 3803/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9070 - val_accuracy: 0.7571\n",
            "Epoch 3804/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9073 - val_accuracy: 0.7571\n",
            "Epoch 3805/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9076 - val_accuracy: 0.7714\n",
            "Epoch 3806/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9079 - val_accuracy: 0.7714\n",
            "Epoch 3807/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9081 - val_accuracy: 0.7714\n",
            "Epoch 3808/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9083 - val_accuracy: 0.7714\n",
            "Epoch 3809/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9084 - val_accuracy: 0.7714\n",
            "Epoch 3810/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9086 - val_accuracy: 0.7714\n",
            "Epoch 3811/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9089 - val_accuracy: 0.7714\n",
            "Epoch 3812/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9092 - val_accuracy: 0.7714\n",
            "Epoch 3813/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9096 - val_accuracy: 0.7714\n",
            "Epoch 3814/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9100 - val_accuracy: 0.7714\n",
            "Epoch 3815/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9103 - val_accuracy: 0.7714\n",
            "Epoch 3816/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9107 - val_accuracy: 0.7714\n",
            "Epoch 3817/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9110 - val_accuracy: 0.7714\n",
            "Epoch 3818/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9112 - val_accuracy: 0.7714\n",
            "Epoch 3819/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9114 - val_accuracy: 0.7714\n",
            "Epoch 3820/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9115 - val_accuracy: 0.7714\n",
            "Epoch 3821/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9117 - val_accuracy: 0.7714\n",
            "Epoch 3822/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9120 - val_accuracy: 0.7714\n",
            "Epoch 3823/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9123 - val_accuracy: 0.7714\n",
            "Epoch 3824/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9126 - val_accuracy: 0.7714\n",
            "Epoch 3825/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9129 - val_accuracy: 0.7714\n",
            "Epoch 3826/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9132 - val_accuracy: 0.7714\n",
            "Epoch 3827/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9135 - val_accuracy: 0.7714\n",
            "Epoch 3828/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9137 - val_accuracy: 0.7714\n",
            "Epoch 3829/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9140 - val_accuracy: 0.7714\n",
            "Epoch 3830/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9142 - val_accuracy: 0.7714\n",
            "Epoch 3831/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9144 - val_accuracy: 0.7714\n",
            "Epoch 3832/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9146 - val_accuracy: 0.7714\n",
            "Epoch 3833/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9149 - val_accuracy: 0.7714\n",
            "Epoch 3834/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9153 - val_accuracy: 0.7714\n",
            "Epoch 3835/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9157 - val_accuracy: 0.7714\n",
            "Epoch 3836/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9160 - val_accuracy: 0.7714\n",
            "Epoch 3837/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9162 - val_accuracy: 0.7714\n",
            "Epoch 3838/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9164 - val_accuracy: 0.7714\n",
            "Epoch 3839/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9167 - val_accuracy: 0.7714\n",
            "Epoch 3840/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0019 - accuracy: 1.0000 - val_loss: 1.9169 - val_accuracy: 0.7714\n",
            "Epoch 3841/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9171 - val_accuracy: 0.7714\n",
            "Epoch 3842/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9173 - val_accuracy: 0.7714\n",
            "Epoch 3843/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9175 - val_accuracy: 0.7714\n",
            "Epoch 3844/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9177 - val_accuracy: 0.7714\n",
            "Epoch 3845/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9181 - val_accuracy: 0.7714\n",
            "Epoch 3846/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9184 - val_accuracy: 0.7714\n",
            "Epoch 3847/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9187 - val_accuracy: 0.7714\n",
            "Epoch 3848/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9190 - val_accuracy: 0.7714\n",
            "Epoch 3849/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9193 - val_accuracy: 0.7714\n",
            "Epoch 3850/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9196 - val_accuracy: 0.7714\n",
            "Epoch 3851/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9198 - val_accuracy: 0.7714\n",
            "Epoch 3852/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9200 - val_accuracy: 0.7714\n",
            "Epoch 3853/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9203 - val_accuracy: 0.7714\n",
            "Epoch 3854/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9206 - val_accuracy: 0.7714\n",
            "Epoch 3855/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9209 - val_accuracy: 0.7714\n",
            "Epoch 3856/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9212 - val_accuracy: 0.7714\n",
            "Epoch 3857/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9215 - val_accuracy: 0.7714\n",
            "Epoch 3858/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9219 - val_accuracy: 0.7714\n",
            "Epoch 3859/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9221 - val_accuracy: 0.7714\n",
            "Epoch 3860/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9224 - val_accuracy: 0.7714\n",
            "Epoch 3861/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9226 - val_accuracy: 0.7714\n",
            "Epoch 3862/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9228 - val_accuracy: 0.7714\n",
            "Epoch 3863/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9230 - val_accuracy: 0.7714\n",
            "Epoch 3864/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9233 - val_accuracy: 0.7714\n",
            "Epoch 3865/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9236 - val_accuracy: 0.7714\n",
            "Epoch 3866/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9239 - val_accuracy: 0.7714\n",
            "Epoch 3867/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9242 - val_accuracy: 0.7714\n",
            "Epoch 3868/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9245 - val_accuracy: 0.7714\n",
            "Epoch 3869/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9247 - val_accuracy: 0.7714\n",
            "Epoch 3870/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9250 - val_accuracy: 0.7714\n",
            "Epoch 3871/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9253 - val_accuracy: 0.7714\n",
            "Epoch 3872/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9256 - val_accuracy: 0.7714\n",
            "Epoch 3873/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9257 - val_accuracy: 0.7714\n",
            "Epoch 3874/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9259 - val_accuracy: 0.7714\n",
            "Epoch 3875/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9261 - val_accuracy: 0.7714\n",
            "Epoch 3876/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9264 - val_accuracy: 0.7714\n",
            "Epoch 3877/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9268 - val_accuracy: 0.7714\n",
            "Epoch 3878/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9271 - val_accuracy: 0.7714\n",
            "Epoch 3879/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9273 - val_accuracy: 0.7714\n",
            "Epoch 3880/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9276 - val_accuracy: 0.7714\n",
            "Epoch 3881/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9279 - val_accuracy: 0.7714\n",
            "Epoch 3882/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9281 - val_accuracy: 0.7714\n",
            "Epoch 3883/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9282 - val_accuracy: 0.7714\n",
            "Epoch 3884/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9284 - val_accuracy: 0.7714\n",
            "Epoch 3885/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9285 - val_accuracy: 0.7714\n",
            "Epoch 3886/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9288 - val_accuracy: 0.7714\n",
            "Epoch 3887/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9292 - val_accuracy: 0.7714\n",
            "Epoch 3888/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9296 - val_accuracy: 0.7714\n",
            "Epoch 3889/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9300 - val_accuracy: 0.7714\n",
            "Epoch 3890/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9302 - val_accuracy: 0.7714\n",
            "Epoch 3891/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9306 - val_accuracy: 0.7714\n",
            "Epoch 3892/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9309 - val_accuracy: 0.7714\n",
            "Epoch 3893/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9311 - val_accuracy: 0.7714\n",
            "Epoch 3894/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9314 - val_accuracy: 0.7714\n",
            "Epoch 3895/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9316 - val_accuracy: 0.7714\n",
            "Epoch 3896/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9318 - val_accuracy: 0.7714\n",
            "Epoch 3897/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9320 - val_accuracy: 0.7714\n",
            "Epoch 3898/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9322 - val_accuracy: 0.7714\n",
            "Epoch 3899/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9325 - val_accuracy: 0.7714\n",
            "Epoch 3900/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9329 - val_accuracy: 0.7714\n",
            "Epoch 3901/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9332 - val_accuracy: 0.7714\n",
            "Epoch 3902/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9334 - val_accuracy: 0.7714\n",
            "Epoch 3903/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9337 - val_accuracy: 0.7714\n",
            "Epoch 3904/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0018 - accuracy: 1.0000 - val_loss: 1.9339 - val_accuracy: 0.7714\n",
            "Epoch 3905/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9341 - val_accuracy: 0.7714\n",
            "Epoch 3906/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9344 - val_accuracy: 0.7714\n",
            "Epoch 3907/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9348 - val_accuracy: 0.7714\n",
            "Epoch 3908/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9351 - val_accuracy: 0.7714\n",
            "Epoch 3909/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9354 - val_accuracy: 0.7714\n",
            "Epoch 3910/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9357 - val_accuracy: 0.7714\n",
            "Epoch 3911/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9360 - val_accuracy: 0.7714\n",
            "Epoch 3912/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9362 - val_accuracy: 0.7714\n",
            "Epoch 3913/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9364 - val_accuracy: 0.7714\n",
            "Epoch 3914/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9367 - val_accuracy: 0.7714\n",
            "Epoch 3915/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9370 - val_accuracy: 0.7714\n",
            "Epoch 3916/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9372 - val_accuracy: 0.7714\n",
            "Epoch 3917/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9374 - val_accuracy: 0.7714\n",
            "Epoch 3918/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9377 - val_accuracy: 0.7714\n",
            "Epoch 3919/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9379 - val_accuracy: 0.7714\n",
            "Epoch 3920/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9383 - val_accuracy: 0.7714\n",
            "Epoch 3921/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9385 - val_accuracy: 0.7714\n",
            "Epoch 3922/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9388 - val_accuracy: 0.7714\n",
            "Epoch 3923/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9390 - val_accuracy: 0.7714\n",
            "Epoch 3924/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9392 - val_accuracy: 0.7714\n",
            "Epoch 3925/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9394 - val_accuracy: 0.7714\n",
            "Epoch 3926/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9397 - val_accuracy: 0.7714\n",
            "Epoch 3927/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9399 - val_accuracy: 0.7714\n",
            "Epoch 3928/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9401 - val_accuracy: 0.7714\n",
            "Epoch 3929/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9405 - val_accuracy: 0.7714\n",
            "Epoch 3930/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9408 - val_accuracy: 0.7714\n",
            "Epoch 3931/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9411 - val_accuracy: 0.7714\n",
            "Epoch 3932/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9414 - val_accuracy: 0.7714\n",
            "Epoch 3933/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9416 - val_accuracy: 0.7714\n",
            "Epoch 3934/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9419 - val_accuracy: 0.7714\n",
            "Epoch 3935/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9421 - val_accuracy: 0.7714\n",
            "Epoch 3936/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9423 - val_accuracy: 0.7714\n",
            "Epoch 3937/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9425 - val_accuracy: 0.7714\n",
            "Epoch 3938/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9426 - val_accuracy: 0.7714\n",
            "Epoch 3939/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9428 - val_accuracy: 0.7714\n",
            "Epoch 3940/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9431 - val_accuracy: 0.7714\n",
            "Epoch 3941/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9436 - val_accuracy: 0.7714\n",
            "Epoch 3942/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9440 - val_accuracy: 0.7714\n",
            "Epoch 3943/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9445 - val_accuracy: 0.7714\n",
            "Epoch 3944/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9449 - val_accuracy: 0.7714\n",
            "Epoch 3945/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9453 - val_accuracy: 0.7714\n",
            "Epoch 3946/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9457 - val_accuracy: 0.7714\n",
            "Epoch 3947/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9460 - val_accuracy: 0.7714\n",
            "Epoch 3948/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9463 - val_accuracy: 0.7714\n",
            "Epoch 3949/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9466 - val_accuracy: 0.7714\n",
            "Epoch 3950/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9468 - val_accuracy: 0.7714\n",
            "Epoch 3951/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9471 - val_accuracy: 0.7714\n",
            "Epoch 3952/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9472 - val_accuracy: 0.7714\n",
            "Epoch 3953/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9473 - val_accuracy: 0.7714\n",
            "Epoch 3954/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9476 - val_accuracy: 0.7714\n",
            "Epoch 3955/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9478 - val_accuracy: 0.7714\n",
            "Epoch 3956/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9480 - val_accuracy: 0.7714\n",
            "Epoch 3957/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9483 - val_accuracy: 0.7714\n",
            "Epoch 3958/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9486 - val_accuracy: 0.7714\n",
            "Epoch 3959/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9488 - val_accuracy: 0.7714\n",
            "Epoch 3960/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9491 - val_accuracy: 0.7714\n",
            "Epoch 3961/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9494 - val_accuracy: 0.7714\n",
            "Epoch 3962/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9498 - val_accuracy: 0.7714\n",
            "Epoch 3963/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9502 - val_accuracy: 0.7714\n",
            "Epoch 3964/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9505 - val_accuracy: 0.7714\n",
            "Epoch 3965/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9507 - val_accuracy: 0.7714\n",
            "Epoch 3966/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9509 - val_accuracy: 0.7714\n",
            "Epoch 3967/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9511 - val_accuracy: 0.7714\n",
            "Epoch 3968/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9514 - val_accuracy: 0.7714\n",
            "Epoch 3969/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9516 - val_accuracy: 0.7714\n",
            "Epoch 3970/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9517 - val_accuracy: 0.7714\n",
            "Epoch 3971/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9519 - val_accuracy: 0.7714\n",
            "Epoch 3972/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0017 - accuracy: 1.0000 - val_loss: 1.9522 - val_accuracy: 0.7714\n",
            "Epoch 3973/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9525 - val_accuracy: 0.7714\n",
            "Epoch 3974/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9528 - val_accuracy: 0.7714\n",
            "Epoch 3975/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9532 - val_accuracy: 0.7714\n",
            "Epoch 3976/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9535 - val_accuracy: 0.7714\n",
            "Epoch 3977/4000\n",
            "1/1 [==============================] - 0s 82ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9538 - val_accuracy: 0.7714\n",
            "Epoch 3978/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9540 - val_accuracy: 0.7714\n",
            "Epoch 3979/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9542 - val_accuracy: 0.7714\n",
            "Epoch 3980/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9544 - val_accuracy: 0.7714\n",
            "Epoch 3981/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9546 - val_accuracy: 0.7714\n",
            "Epoch 3982/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9549 - val_accuracy: 0.7714\n",
            "Epoch 3983/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9552 - val_accuracy: 0.7714\n",
            "Epoch 3984/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9555 - val_accuracy: 0.7714\n",
            "Epoch 3985/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9557 - val_accuracy: 0.7714\n",
            "Epoch 3986/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9560 - val_accuracy: 0.7714\n",
            "Epoch 3987/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9562 - val_accuracy: 0.7714\n",
            "Epoch 3988/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9565 - val_accuracy: 0.7714\n",
            "Epoch 3989/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9567 - val_accuracy: 0.7714\n",
            "Epoch 3990/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9570 - val_accuracy: 0.7714\n",
            "Epoch 3991/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9573 - val_accuracy: 0.7714\n",
            "Epoch 3992/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9575 - val_accuracy: 0.7714\n",
            "Epoch 3993/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9578 - val_accuracy: 0.7714\n",
            "Epoch 3994/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9581 - val_accuracy: 0.7714\n",
            "Epoch 3995/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9584 - val_accuracy: 0.7714\n",
            "Epoch 3996/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9587 - val_accuracy: 0.7714\n",
            "Epoch 3997/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9590 - val_accuracy: 0.7714\n",
            "Epoch 3998/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9593 - val_accuracy: 0.7714\n",
            "Epoch 3999/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9595 - val_accuracy: 0.7714\n",
            "Epoch 4000/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.0016 - accuracy: 1.0000 - val_loss: 1.9596 - val_accuracy: 0.7714\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "9Xa3XfXX-Eht"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "WqiV_Ugb-EnQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# evaluate the model\n",
        "_, train_acc = model.evaluate(trainX, trainy, verbose=0)\n",
        "_, test_acc = model.evaluate(testX, testy, verbose=0)\n",
        "print('Train: %.3f, Test: %.3f' % (train_acc, test_acc))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LrYxsQUC9n7s",
        "outputId": "d78a0576-9e2e-403a-e590-fa764ad6af77"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Train: 1.000, Test: 0.771\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot history\n",
        "pyplot.plot(history.history['accuracy'], label='train')\n",
        "pyplot.plot(history.history['val_accuracy'], label='test')\n",
        "pyplot.legend()\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "luqb2zUV-F5f",
        "outputId": "2e1e8749-496c-4bc7-81c6-c350e823a3a2"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Overfit MLP With Dropout Regularization**"
      ],
      "metadata": {
        "id": "8UKtgTCF-Lrd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# define model\n",
        "model = Sequential()\n",
        "model.add(Dense(500, input_dim=2, activation='relu'))\n",
        "model.add(Dropout(0.4))\n",
        "model.add(Dense(1, activation='sigmoid'))\n",
        "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "hLpvnxns-GFR"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# fit model\n",
        "history = model.fit(trainX, trainy, validation_data=(testX, testy), epochs=4000, verbose=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C-NWL_AJ_D1d",
        "outputId": "050c11b8-29b1-4d06-f466-20c790ac324b"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3583 - accuracy: 0.8000 - val_loss: 0.4897 - val_accuracy: 0.7429\n",
            "Epoch 1502/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.3087 - accuracy: 0.8667 - val_loss: 0.4897 - val_accuracy: 0.7571\n",
            "Epoch 1503/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2599 - accuracy: 0.9333 - val_loss: 0.4899 - val_accuracy: 0.7571\n",
            "Epoch 1504/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2660 - accuracy: 0.9000 - val_loss: 0.4902 - val_accuracy: 0.7571\n",
            "Epoch 1505/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2357 - accuracy: 0.9333 - val_loss: 0.4902 - val_accuracy: 0.7571\n",
            "Epoch 1506/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2577 - accuracy: 0.9333 - val_loss: 0.4908 - val_accuracy: 0.7571\n",
            "Epoch 1507/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2891 - accuracy: 0.8667 - val_loss: 0.4916 - val_accuracy: 0.7429\n",
            "Epoch 1508/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3031 - accuracy: 0.8333 - val_loss: 0.4931 - val_accuracy: 0.7429\n",
            "Epoch 1509/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.3377 - accuracy: 0.8667 - val_loss: 0.4938 - val_accuracy: 0.7429\n",
            "Epoch 1510/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.3121 - accuracy: 0.9000 - val_loss: 0.4953 - val_accuracy: 0.7429\n",
            "Epoch 1511/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2778 - accuracy: 0.9333 - val_loss: 0.4966 - val_accuracy: 0.7429\n",
            "Epoch 1512/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2358 - accuracy: 0.9333 - val_loss: 0.4983 - val_accuracy: 0.7429\n",
            "Epoch 1513/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2792 - accuracy: 0.8667 - val_loss: 0.5009 - val_accuracy: 0.7429\n",
            "Epoch 1514/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2862 - accuracy: 0.8667 - val_loss: 0.5025 - val_accuracy: 0.7429\n",
            "Epoch 1515/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2965 - accuracy: 0.8333 - val_loss: 0.5038 - val_accuracy: 0.7429\n",
            "Epoch 1516/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2637 - accuracy: 0.9000 - val_loss: 0.5053 - val_accuracy: 0.7429\n",
            "Epoch 1517/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2951 - accuracy: 0.8667 - val_loss: 0.5065 - val_accuracy: 0.7429\n",
            "Epoch 1518/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.2978 - accuracy: 0.9000 - val_loss: 0.5065 - val_accuracy: 0.7429\n",
            "Epoch 1519/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2883 - accuracy: 0.8667 - val_loss: 0.5068 - val_accuracy: 0.7429\n",
            "Epoch 1520/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3031 - accuracy: 0.8667 - val_loss: 0.5057 - val_accuracy: 0.7429\n",
            "Epoch 1521/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2523 - accuracy: 0.9000 - val_loss: 0.5035 - val_accuracy: 0.7429\n",
            "Epoch 1522/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2681 - accuracy: 0.9000 - val_loss: 0.5021 - val_accuracy: 0.7429\n",
            "Epoch 1523/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2910 - accuracy: 0.9333 - val_loss: 0.5015 - val_accuracy: 0.7429\n",
            "Epoch 1524/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2638 - accuracy: 0.9000 - val_loss: 0.5015 - val_accuracy: 0.7429\n",
            "Epoch 1525/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.3494 - accuracy: 0.7667 - val_loss: 0.5016 - val_accuracy: 0.7429\n",
            "Epoch 1526/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.3244 - accuracy: 0.9000 - val_loss: 0.5004 - val_accuracy: 0.7429\n",
            "Epoch 1527/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.3332 - accuracy: 0.8333 - val_loss: 0.4987 - val_accuracy: 0.7429\n",
            "Epoch 1528/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3129 - accuracy: 0.8667 - val_loss: 0.4973 - val_accuracy: 0.7429\n",
            "Epoch 1529/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3242 - accuracy: 0.9333 - val_loss: 0.4967 - val_accuracy: 0.7571\n",
            "Epoch 1530/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2670 - accuracy: 0.9000 - val_loss: 0.4962 - val_accuracy: 0.7571\n",
            "Epoch 1531/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3607 - accuracy: 0.8333 - val_loss: 0.4962 - val_accuracy: 0.7571\n",
            "Epoch 1532/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2998 - accuracy: 0.9000 - val_loss: 0.4961 - val_accuracy: 0.7571\n",
            "Epoch 1533/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2804 - accuracy: 0.9000 - val_loss: 0.4967 - val_accuracy: 0.7571\n",
            "Epoch 1534/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2537 - accuracy: 0.9333 - val_loss: 0.4973 - val_accuracy: 0.7571\n",
            "Epoch 1535/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2878 - accuracy: 0.9000 - val_loss: 0.4978 - val_accuracy: 0.7571\n",
            "Epoch 1536/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2723 - accuracy: 0.9000 - val_loss: 0.4974 - val_accuracy: 0.7571\n",
            "Epoch 1537/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3253 - accuracy: 0.8667 - val_loss: 0.4972 - val_accuracy: 0.7571\n",
            "Epoch 1538/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2902 - accuracy: 0.9667 - val_loss: 0.4986 - val_accuracy: 0.7571\n",
            "Epoch 1539/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2801 - accuracy: 0.9000 - val_loss: 0.4995 - val_accuracy: 0.7571\n",
            "Epoch 1540/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2668 - accuracy: 0.9000 - val_loss: 0.4998 - val_accuracy: 0.7571\n",
            "Epoch 1541/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.3597 - accuracy: 0.8333 - val_loss: 0.4999 - val_accuracy: 0.7571\n",
            "Epoch 1542/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2553 - accuracy: 0.9333 - val_loss: 0.4998 - val_accuracy: 0.7571\n",
            "Epoch 1543/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2408 - accuracy: 0.9333 - val_loss: 0.4998 - val_accuracy: 0.7571\n",
            "Epoch 1544/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2934 - accuracy: 0.9000 - val_loss: 0.4991 - val_accuracy: 0.7571\n",
            "Epoch 1545/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2334 - accuracy: 0.9667 - val_loss: 0.4991 - val_accuracy: 0.7571\n",
            "Epoch 1546/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3447 - accuracy: 0.8333 - val_loss: 0.5001 - val_accuracy: 0.7571\n",
            "Epoch 1547/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.3389 - accuracy: 0.8333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 1548/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1890 - accuracy: 1.0000 - val_loss: 0.5042 - val_accuracy: 0.7571\n",
            "Epoch 1549/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2370 - accuracy: 0.9667 - val_loss: 0.5071 - val_accuracy: 0.7429\n",
            "Epoch 1550/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2833 - accuracy: 0.8333 - val_loss: 0.5088 - val_accuracy: 0.7429\n",
            "Epoch 1551/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2815 - accuracy: 0.8667 - val_loss: 0.5097 - val_accuracy: 0.7429\n",
            "Epoch 1552/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.3032 - accuracy: 0.8000 - val_loss: 0.5101 - val_accuracy: 0.7429\n",
            "Epoch 1553/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2911 - accuracy: 0.9000 - val_loss: 0.5102 - val_accuracy: 0.7429\n",
            "Epoch 1554/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3029 - accuracy: 0.9000 - val_loss: 0.5111 - val_accuracy: 0.7429\n",
            "Epoch 1555/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3076 - accuracy: 0.8000 - val_loss: 0.5124 - val_accuracy: 0.7429\n",
            "Epoch 1556/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2601 - accuracy: 0.8667 - val_loss: 0.5149 - val_accuracy: 0.7429\n",
            "Epoch 1557/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3784 - accuracy: 0.8333 - val_loss: 0.5165 - val_accuracy: 0.7429\n",
            "Epoch 1558/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2266 - accuracy: 0.9333 - val_loss: 0.5175 - val_accuracy: 0.7286\n",
            "Epoch 1559/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2350 - accuracy: 0.9333 - val_loss: 0.5184 - val_accuracy: 0.7286\n",
            "Epoch 1560/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2602 - accuracy: 0.9667 - val_loss: 0.5175 - val_accuracy: 0.7286\n",
            "Epoch 1561/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2861 - accuracy: 0.9000 - val_loss: 0.5167 - val_accuracy: 0.7286\n",
            "Epoch 1562/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.3111 - accuracy: 0.8667 - val_loss: 0.5159 - val_accuracy: 0.7429\n",
            "Epoch 1563/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.3649 - accuracy: 0.8333 - val_loss: 0.5151 - val_accuracy: 0.7429\n",
            "Epoch 1564/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2362 - accuracy: 0.9333 - val_loss: 0.5133 - val_accuracy: 0.7429\n",
            "Epoch 1565/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.3073 - accuracy: 0.8667 - val_loss: 0.5115 - val_accuracy: 0.7429\n",
            "Epoch 1566/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.3122 - accuracy: 0.8000 - val_loss: 0.5089 - val_accuracy: 0.7429\n",
            "Epoch 1567/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2331 - accuracy: 0.9333 - val_loss: 0.5061 - val_accuracy: 0.7429\n",
            "Epoch 1568/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3575 - accuracy: 0.8333 - val_loss: 0.5050 - val_accuracy: 0.7571\n",
            "Epoch 1569/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2724 - accuracy: 0.9000 - val_loss: 0.5040 - val_accuracy: 0.7571\n",
            "Epoch 1570/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2324 - accuracy: 0.9333 - val_loss: 0.5039 - val_accuracy: 0.7571\n",
            "Epoch 1571/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.2879 - accuracy: 0.9000 - val_loss: 0.5034 - val_accuracy: 0.7571\n",
            "Epoch 1572/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3809 - accuracy: 0.7667 - val_loss: 0.5038 - val_accuracy: 0.7571\n",
            "Epoch 1573/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2422 - accuracy: 0.9000 - val_loss: 0.5048 - val_accuracy: 0.7571\n",
            "Epoch 1574/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1979 - accuracy: 1.0000 - val_loss: 0.5055 - val_accuracy: 0.7571\n",
            "Epoch 1575/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.3155 - accuracy: 0.8667 - val_loss: 0.5053 - val_accuracy: 0.7429\n",
            "Epoch 1576/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2459 - accuracy: 0.9333 - val_loss: 0.5055 - val_accuracy: 0.7429\n",
            "Epoch 1577/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3199 - accuracy: 0.8333 - val_loss: 0.5056 - val_accuracy: 0.7429\n",
            "Epoch 1578/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2971 - accuracy: 0.9000 - val_loss: 0.5062 - val_accuracy: 0.7429\n",
            "Epoch 1579/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2489 - accuracy: 0.9333 - val_loss: 0.5071 - val_accuracy: 0.7429\n",
            "Epoch 1580/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.3187 - accuracy: 0.9000 - val_loss: 0.5073 - val_accuracy: 0.7429\n",
            "Epoch 1581/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2919 - accuracy: 0.8667 - val_loss: 0.5073 - val_accuracy: 0.7429\n",
            "Epoch 1582/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2610 - accuracy: 0.8667 - val_loss: 0.5072 - val_accuracy: 0.7429\n",
            "Epoch 1583/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2761 - accuracy: 0.8667 - val_loss: 0.5063 - val_accuracy: 0.7429\n",
            "Epoch 1584/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2960 - accuracy: 0.8667 - val_loss: 0.5051 - val_accuracy: 0.7429\n",
            "Epoch 1585/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2551 - accuracy: 0.9000 - val_loss: 0.5033 - val_accuracy: 0.7429\n",
            "Epoch 1586/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2137 - accuracy: 0.9667 - val_loss: 0.5022 - val_accuracy: 0.7429\n",
            "Epoch 1587/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2612 - accuracy: 0.9667 - val_loss: 0.5008 - val_accuracy: 0.7571\n",
            "Epoch 1588/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2854 - accuracy: 0.9333 - val_loss: 0.4987 - val_accuracy: 0.7571\n",
            "Epoch 1589/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3035 - accuracy: 0.8667 - val_loss: 0.4958 - val_accuracy: 0.7571\n",
            "Epoch 1590/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2570 - accuracy: 0.9333 - val_loss: 0.4931 - val_accuracy: 0.7571\n",
            "Epoch 1591/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3331 - accuracy: 0.8667 - val_loss: 0.4913 - val_accuracy: 0.7571\n",
            "Epoch 1592/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2927 - accuracy: 0.9000 - val_loss: 0.4899 - val_accuracy: 0.7571\n",
            "Epoch 1593/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2697 - accuracy: 0.9333 - val_loss: 0.4885 - val_accuracy: 0.7714\n",
            "Epoch 1594/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1765 - accuracy: 0.9667 - val_loss: 0.4877 - val_accuracy: 0.7714\n",
            "Epoch 1595/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2904 - accuracy: 0.9000 - val_loss: 0.4882 - val_accuracy: 0.7714\n",
            "Epoch 1596/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2387 - accuracy: 0.9667 - val_loss: 0.4887 - val_accuracy: 0.7714\n",
            "Epoch 1597/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3398 - accuracy: 0.9000 - val_loss: 0.4893 - val_accuracy: 0.7714\n",
            "Epoch 1598/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2473 - accuracy: 0.9333 - val_loss: 0.4911 - val_accuracy: 0.7714\n",
            "Epoch 1599/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2558 - accuracy: 0.9333 - val_loss: 0.4916 - val_accuracy: 0.7714\n",
            "Epoch 1600/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2497 - accuracy: 0.9333 - val_loss: 0.4926 - val_accuracy: 0.7714\n",
            "Epoch 1601/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2229 - accuracy: 0.9667 - val_loss: 0.4929 - val_accuracy: 0.7714\n",
            "Epoch 1602/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2291 - accuracy: 0.9000 - val_loss: 0.4934 - val_accuracy: 0.7714\n",
            "Epoch 1603/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2697 - accuracy: 0.9000 - val_loss: 0.4942 - val_accuracy: 0.7714\n",
            "Epoch 1604/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2685 - accuracy: 0.9000 - val_loss: 0.4951 - val_accuracy: 0.7714\n",
            "Epoch 1605/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2822 - accuracy: 0.9333 - val_loss: 0.4972 - val_accuracy: 0.7571\n",
            "Epoch 1606/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2827 - accuracy: 0.9333 - val_loss: 0.4988 - val_accuracy: 0.7571\n",
            "Epoch 1607/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2409 - accuracy: 0.9333 - val_loss: 0.4995 - val_accuracy: 0.7571\n",
            "Epoch 1608/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2727 - accuracy: 0.8667 - val_loss: 0.4988 - val_accuracy: 0.7571\n",
            "Epoch 1609/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2118 - accuracy: 0.9333 - val_loss: 0.4982 - val_accuracy: 0.7714\n",
            "Epoch 1610/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2920 - accuracy: 0.8667 - val_loss: 0.4975 - val_accuracy: 0.7714\n",
            "Epoch 1611/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2260 - accuracy: 0.9333 - val_loss: 0.4967 - val_accuracy: 0.7714\n",
            "Epoch 1612/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2453 - accuracy: 0.9000 - val_loss: 0.4963 - val_accuracy: 0.7714\n",
            "Epoch 1613/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2582 - accuracy: 0.9667 - val_loss: 0.4958 - val_accuracy: 0.7714\n",
            "Epoch 1614/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2547 - accuracy: 0.9000 - val_loss: 0.4959 - val_accuracy: 0.7714\n",
            "Epoch 1615/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2038 - accuracy: 0.9667 - val_loss: 0.4962 - val_accuracy: 0.7714\n",
            "Epoch 1616/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2697 - accuracy: 0.9000 - val_loss: 0.4967 - val_accuracy: 0.7714\n",
            "Epoch 1617/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2773 - accuracy: 0.9000 - val_loss: 0.4963 - val_accuracy: 0.7714\n",
            "Epoch 1618/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3504 - accuracy: 0.8333 - val_loss: 0.4956 - val_accuracy: 0.7714\n",
            "Epoch 1619/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.4013 - accuracy: 0.8000 - val_loss: 0.4935 - val_accuracy: 0.7714\n",
            "Epoch 1620/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2847 - accuracy: 0.9000 - val_loss: 0.4917 - val_accuracy: 0.7714\n",
            "Epoch 1621/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2289 - accuracy: 0.9333 - val_loss: 0.4904 - val_accuracy: 0.7714\n",
            "Epoch 1622/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2798 - accuracy: 0.8333 - val_loss: 0.4884 - val_accuracy: 0.7714\n",
            "Epoch 1623/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2625 - accuracy: 0.9000 - val_loss: 0.4865 - val_accuracy: 0.7714\n",
            "Epoch 1624/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.3305 - accuracy: 0.9000 - val_loss: 0.4855 - val_accuracy: 0.7714\n",
            "Epoch 1625/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.2493 - accuracy: 0.9667 - val_loss: 0.4860 - val_accuracy: 0.7714\n",
            "Epoch 1626/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.3069 - accuracy: 0.8333 - val_loss: 0.4875 - val_accuracy: 0.7714\n",
            "Epoch 1627/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2197 - accuracy: 0.9667 - val_loss: 0.4891 - val_accuracy: 0.7714\n",
            "Epoch 1628/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3288 - accuracy: 0.8333 - val_loss: 0.4912 - val_accuracy: 0.7714\n",
            "Epoch 1629/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2371 - accuracy: 0.9333 - val_loss: 0.4934 - val_accuracy: 0.7571\n",
            "Epoch 1630/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.3817 - accuracy: 0.7667 - val_loss: 0.4950 - val_accuracy: 0.7571\n",
            "Epoch 1631/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2885 - accuracy: 0.9333 - val_loss: 0.4959 - val_accuracy: 0.7571\n",
            "Epoch 1632/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1840 - accuracy: 0.9667 - val_loss: 0.4966 - val_accuracy: 0.7571\n",
            "Epoch 1633/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2581 - accuracy: 0.9667 - val_loss: 0.4969 - val_accuracy: 0.7571\n",
            "Epoch 1634/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2729 - accuracy: 0.8667 - val_loss: 0.4971 - val_accuracy: 0.7714\n",
            "Epoch 1635/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2230 - accuracy: 0.9000 - val_loss: 0.4975 - val_accuracy: 0.7714\n",
            "Epoch 1636/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2534 - accuracy: 0.9667 - val_loss: 0.4984 - val_accuracy: 0.7714\n",
            "Epoch 1637/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2491 - accuracy: 0.9000 - val_loss: 0.5003 - val_accuracy: 0.7714\n",
            "Epoch 1638/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2888 - accuracy: 0.9333 - val_loss: 0.5017 - val_accuracy: 0.7571\n",
            "Epoch 1639/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2140 - accuracy: 0.9333 - val_loss: 0.5035 - val_accuracy: 0.7571\n",
            "Epoch 1640/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2829 - accuracy: 0.9333 - val_loss: 0.5042 - val_accuracy: 0.7571\n",
            "Epoch 1641/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2619 - accuracy: 0.9000 - val_loss: 0.5052 - val_accuracy: 0.7571\n",
            "Epoch 1642/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2875 - accuracy: 0.9667 - val_loss: 0.5074 - val_accuracy: 0.7571\n",
            "Epoch 1643/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2611 - accuracy: 0.9333 - val_loss: 0.5102 - val_accuracy: 0.7571\n",
            "Epoch 1644/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2847 - accuracy: 0.9000 - val_loss: 0.5129 - val_accuracy: 0.7571\n",
            "Epoch 1645/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2840 - accuracy: 0.9000 - val_loss: 0.5149 - val_accuracy: 0.7571\n",
            "Epoch 1646/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2892 - accuracy: 0.9000 - val_loss: 0.5178 - val_accuracy: 0.7429\n",
            "Epoch 1647/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2644 - accuracy: 0.9000 - val_loss: 0.5202 - val_accuracy: 0.7286\n",
            "Epoch 1648/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2777 - accuracy: 0.8667 - val_loss: 0.5208 - val_accuracy: 0.7286\n",
            "Epoch 1649/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3106 - accuracy: 0.9333 - val_loss: 0.5200 - val_accuracy: 0.7286\n",
            "Epoch 1650/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2842 - accuracy: 0.8667 - val_loss: 0.5192 - val_accuracy: 0.7286\n",
            "Epoch 1651/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2834 - accuracy: 0.9000 - val_loss: 0.5172 - val_accuracy: 0.7286\n",
            "Epoch 1652/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2170 - accuracy: 0.9333 - val_loss: 0.5146 - val_accuracy: 0.7429\n",
            "Epoch 1653/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3064 - accuracy: 0.9000 - val_loss: 0.5116 - val_accuracy: 0.7429\n",
            "Epoch 1654/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2390 - accuracy: 0.9000 - val_loss: 0.5092 - val_accuracy: 0.7429\n",
            "Epoch 1655/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1788 - accuracy: 0.9667 - val_loss: 0.5069 - val_accuracy: 0.7571\n",
            "Epoch 1656/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2545 - accuracy: 0.9333 - val_loss: 0.5047 - val_accuracy: 0.7571\n",
            "Epoch 1657/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2537 - accuracy: 0.9000 - val_loss: 0.5018 - val_accuracy: 0.7571\n",
            "Epoch 1658/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3396 - accuracy: 0.8000 - val_loss: 0.4997 - val_accuracy: 0.7571\n",
            "Epoch 1659/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2336 - accuracy: 0.9333 - val_loss: 0.4983 - val_accuracy: 0.7571\n",
            "Epoch 1660/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2459 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7571\n",
            "Epoch 1661/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2431 - accuracy: 0.9667 - val_loss: 0.4980 - val_accuracy: 0.7571\n",
            "Epoch 1662/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2394 - accuracy: 0.9000 - val_loss: 0.4986 - val_accuracy: 0.7571\n",
            "Epoch 1663/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1792 - accuracy: 0.9667 - val_loss: 0.4998 - val_accuracy: 0.7571\n",
            "Epoch 1664/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2740 - accuracy: 0.9667 - val_loss: 0.5005 - val_accuracy: 0.7571\n",
            "Epoch 1665/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2815 - accuracy: 0.9333 - val_loss: 0.5002 - val_accuracy: 0.7571\n",
            "Epoch 1666/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2317 - accuracy: 0.9667 - val_loss: 0.5002 - val_accuracy: 0.7571\n",
            "Epoch 1667/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3300 - accuracy: 0.8667 - val_loss: 0.5002 - val_accuracy: 0.7571\n",
            "Epoch 1668/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2608 - accuracy: 0.9000 - val_loss: 0.5013 - val_accuracy: 0.7571\n",
            "Epoch 1669/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3053 - accuracy: 0.9000 - val_loss: 0.5016 - val_accuracy: 0.7571\n",
            "Epoch 1670/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2766 - accuracy: 0.9333 - val_loss: 0.5021 - val_accuracy: 0.7571\n",
            "Epoch 1671/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3117 - accuracy: 0.8000 - val_loss: 0.5037 - val_accuracy: 0.7571\n",
            "Epoch 1672/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2594 - accuracy: 0.9000 - val_loss: 0.5054 - val_accuracy: 0.7571\n",
            "Epoch 1673/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2040 - accuracy: 0.9333 - val_loss: 0.5081 - val_accuracy: 0.7429\n",
            "Epoch 1674/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2806 - accuracy: 0.8667 - val_loss: 0.5105 - val_accuracy: 0.7286\n",
            "Epoch 1675/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2339 - accuracy: 0.9667 - val_loss: 0.5119 - val_accuracy: 0.7286\n",
            "Epoch 1676/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2551 - accuracy: 0.9000 - val_loss: 0.5119 - val_accuracy: 0.7286\n",
            "Epoch 1677/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2414 - accuracy: 0.9333 - val_loss: 0.5124 - val_accuracy: 0.7286\n",
            "Epoch 1678/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2448 - accuracy: 0.9000 - val_loss: 0.5139 - val_accuracy: 0.7286\n",
            "Epoch 1679/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2736 - accuracy: 0.9000 - val_loss: 0.5150 - val_accuracy: 0.7286\n",
            "Epoch 1680/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2662 - accuracy: 0.9000 - val_loss: 0.5157 - val_accuracy: 0.7286\n",
            "Epoch 1681/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2709 - accuracy: 0.9333 - val_loss: 0.5162 - val_accuracy: 0.7286\n",
            "Epoch 1682/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2334 - accuracy: 0.9667 - val_loss: 0.5172 - val_accuracy: 0.7286\n",
            "Epoch 1683/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2525 - accuracy: 0.9000 - val_loss: 0.5171 - val_accuracy: 0.7286\n",
            "Epoch 1684/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3096 - accuracy: 0.9000 - val_loss: 0.5163 - val_accuracy: 0.7286\n",
            "Epoch 1685/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3431 - accuracy: 0.8667 - val_loss: 0.5153 - val_accuracy: 0.7286\n",
            "Epoch 1686/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2295 - accuracy: 0.8667 - val_loss: 0.5141 - val_accuracy: 0.7286\n",
            "Epoch 1687/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3030 - accuracy: 0.9000 - val_loss: 0.5130 - val_accuracy: 0.7286\n",
            "Epoch 1688/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2810 - accuracy: 0.9000 - val_loss: 0.5130 - val_accuracy: 0.7286\n",
            "Epoch 1689/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2608 - accuracy: 0.9000 - val_loss: 0.5110 - val_accuracy: 0.7286\n",
            "Epoch 1690/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2399 - accuracy: 0.9667 - val_loss: 0.5088 - val_accuracy: 0.7286\n",
            "Epoch 1691/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2794 - accuracy: 0.9000 - val_loss: 0.5049 - val_accuracy: 0.7429\n",
            "Epoch 1692/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3636 - accuracy: 0.8667 - val_loss: 0.5007 - val_accuracy: 0.7571\n",
            "Epoch 1693/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2925 - accuracy: 0.9000 - val_loss: 0.4978 - val_accuracy: 0.7571\n",
            "Epoch 1694/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3210 - accuracy: 0.8333 - val_loss: 0.4942 - val_accuracy: 0.7714\n",
            "Epoch 1695/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3584 - accuracy: 0.8667 - val_loss: 0.4913 - val_accuracy: 0.7571\n",
            "Epoch 1696/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2172 - accuracy: 0.9000 - val_loss: 0.4891 - val_accuracy: 0.7429\n",
            "Epoch 1697/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2039 - accuracy: 0.9333 - val_loss: 0.4869 - val_accuracy: 0.7571\n",
            "Epoch 1698/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2370 - accuracy: 0.9667 - val_loss: 0.4853 - val_accuracy: 0.7571\n",
            "Epoch 1699/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3025 - accuracy: 0.8333 - val_loss: 0.4846 - val_accuracy: 0.7571\n",
            "Epoch 1700/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2343 - accuracy: 0.9333 - val_loss: 0.4837 - val_accuracy: 0.7571\n",
            "Epoch 1701/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2785 - accuracy: 0.9000 - val_loss: 0.4833 - val_accuracy: 0.7571\n",
            "Epoch 1702/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2717 - accuracy: 0.9333 - val_loss: 0.4820 - val_accuracy: 0.7714\n",
            "Epoch 1703/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2222 - accuracy: 0.9333 - val_loss: 0.4817 - val_accuracy: 0.7714\n",
            "Epoch 1704/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2194 - accuracy: 0.9333 - val_loss: 0.4812 - val_accuracy: 0.7714\n",
            "Epoch 1705/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2287 - accuracy: 0.9333 - val_loss: 0.4825 - val_accuracy: 0.7714\n",
            "Epoch 1706/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3224 - accuracy: 0.8333 - val_loss: 0.4844 - val_accuracy: 0.7714\n",
            "Epoch 1707/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.3306 - accuracy: 0.8000 - val_loss: 0.4877 - val_accuracy: 0.7714\n",
            "Epoch 1708/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2967 - accuracy: 0.9000 - val_loss: 0.4916 - val_accuracy: 0.7714\n",
            "Epoch 1709/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2130 - accuracy: 0.9667 - val_loss: 0.4959 - val_accuracy: 0.7429\n",
            "Epoch 1710/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2315 - accuracy: 0.9000 - val_loss: 0.4996 - val_accuracy: 0.7429\n",
            "Epoch 1711/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2180 - accuracy: 0.9000 - val_loss: 0.5036 - val_accuracy: 0.7286\n",
            "Epoch 1712/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2104 - accuracy: 0.9667 - val_loss: 0.5073 - val_accuracy: 0.7286\n",
            "Epoch 1713/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2735 - accuracy: 0.9000 - val_loss: 0.5098 - val_accuracy: 0.7286\n",
            "Epoch 1714/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3250 - accuracy: 0.8667 - val_loss: 0.5130 - val_accuracy: 0.7286\n",
            "Epoch 1715/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2232 - accuracy: 0.9333 - val_loss: 0.5149 - val_accuracy: 0.7286\n",
            "Epoch 1716/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2766 - accuracy: 0.9333 - val_loss: 0.5163 - val_accuracy: 0.7286\n",
            "Epoch 1717/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2497 - accuracy: 0.8333 - val_loss: 0.5160 - val_accuracy: 0.7286\n",
            "Epoch 1718/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2419 - accuracy: 0.9333 - val_loss: 0.5150 - val_accuracy: 0.7286\n",
            "Epoch 1719/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2361 - accuracy: 0.9667 - val_loss: 0.5147 - val_accuracy: 0.7286\n",
            "Epoch 1720/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.2301 - accuracy: 0.9333 - val_loss: 0.5132 - val_accuracy: 0.7286\n",
            "Epoch 1721/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2942 - accuracy: 0.8333 - val_loss: 0.5126 - val_accuracy: 0.7286\n",
            "Epoch 1722/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2283 - accuracy: 0.9333 - val_loss: 0.5122 - val_accuracy: 0.7286\n",
            "Epoch 1723/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2129 - accuracy: 0.9000 - val_loss: 0.5116 - val_accuracy: 0.7286\n",
            "Epoch 1724/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2369 - accuracy: 0.9333 - val_loss: 0.5090 - val_accuracy: 0.7286\n",
            "Epoch 1725/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2721 - accuracy: 0.9333 - val_loss: 0.5073 - val_accuracy: 0.7286\n",
            "Epoch 1726/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2835 - accuracy: 0.8667 - val_loss: 0.5067 - val_accuracy: 0.7286\n",
            "Epoch 1727/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2183 - accuracy: 0.9333 - val_loss: 0.5064 - val_accuracy: 0.7286\n",
            "Epoch 1728/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2951 - accuracy: 0.9000 - val_loss: 0.5050 - val_accuracy: 0.7286\n",
            "Epoch 1729/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2756 - accuracy: 0.9333 - val_loss: 0.5045 - val_accuracy: 0.7286\n",
            "Epoch 1730/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.4023 - accuracy: 0.8333 - val_loss: 0.5044 - val_accuracy: 0.7286\n",
            "Epoch 1731/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2667 - accuracy: 0.9000 - val_loss: 0.5034 - val_accuracy: 0.7286\n",
            "Epoch 1732/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2157 - accuracy: 0.9667 - val_loss: 0.5033 - val_accuracy: 0.7286\n",
            "Epoch 1733/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.3418 - accuracy: 0.8667 - val_loss: 0.5040 - val_accuracy: 0.7286\n",
            "Epoch 1734/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.3511 - accuracy: 0.8667 - val_loss: 0.5055 - val_accuracy: 0.7286\n",
            "Epoch 1735/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2585 - accuracy: 0.9000 - val_loss: 0.5071 - val_accuracy: 0.7286\n",
            "Epoch 1736/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3042 - accuracy: 0.9000 - val_loss: 0.5087 - val_accuracy: 0.7286\n",
            "Epoch 1737/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2211 - accuracy: 0.9000 - val_loss: 0.5095 - val_accuracy: 0.7286\n",
            "Epoch 1738/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3006 - accuracy: 0.9000 - val_loss: 0.5096 - val_accuracy: 0.7286\n",
            "Epoch 1739/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2950 - accuracy: 0.8667 - val_loss: 0.5108 - val_accuracy: 0.7286\n",
            "Epoch 1740/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2949 - accuracy: 0.9000 - val_loss: 0.5112 - val_accuracy: 0.7286\n",
            "Epoch 1741/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.3240 - accuracy: 0.9333 - val_loss: 0.5099 - val_accuracy: 0.7286\n",
            "Epoch 1742/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2407 - accuracy: 0.9333 - val_loss: 0.5094 - val_accuracy: 0.7286\n",
            "Epoch 1743/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3142 - accuracy: 0.8667 - val_loss: 0.5079 - val_accuracy: 0.7571\n",
            "Epoch 1744/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2322 - accuracy: 0.9000 - val_loss: 0.5068 - val_accuracy: 0.7571\n",
            "Epoch 1745/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3180 - accuracy: 0.9000 - val_loss: 0.5055 - val_accuracy: 0.7571\n",
            "Epoch 1746/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3082 - accuracy: 0.8667 - val_loss: 0.5035 - val_accuracy: 0.7714\n",
            "Epoch 1747/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2224 - accuracy: 0.9333 - val_loss: 0.5012 - val_accuracy: 0.7714\n",
            "Epoch 1748/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2832 - accuracy: 0.9000 - val_loss: 0.4987 - val_accuracy: 0.7714\n",
            "Epoch 1749/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2436 - accuracy: 0.9667 - val_loss: 0.4962 - val_accuracy: 0.7714\n",
            "Epoch 1750/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2386 - accuracy: 0.9333 - val_loss: 0.4943 - val_accuracy: 0.7714\n",
            "Epoch 1751/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2636 - accuracy: 0.9333 - val_loss: 0.4923 - val_accuracy: 0.7714\n",
            "Epoch 1752/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2449 - accuracy: 0.9333 - val_loss: 0.4911 - val_accuracy: 0.7714\n",
            "Epoch 1753/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2932 - accuracy: 0.9000 - val_loss: 0.4902 - val_accuracy: 0.7714\n",
            "Epoch 1754/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2584 - accuracy: 0.9333 - val_loss: 0.4909 - val_accuracy: 0.7714\n",
            "Epoch 1755/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2666 - accuracy: 0.9333 - val_loss: 0.4924 - val_accuracy: 0.7714\n",
            "Epoch 1756/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2970 - accuracy: 0.8333 - val_loss: 0.4945 - val_accuracy: 0.7714\n",
            "Epoch 1757/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2238 - accuracy: 0.9333 - val_loss: 0.4964 - val_accuracy: 0.7714\n",
            "Epoch 1758/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2613 - accuracy: 0.9667 - val_loss: 0.4984 - val_accuracy: 0.7714\n",
            "Epoch 1759/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2790 - accuracy: 0.9333 - val_loss: 0.4986 - val_accuracy: 0.7714\n",
            "Epoch 1760/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2551 - accuracy: 0.9333 - val_loss: 0.4982 - val_accuracy: 0.7714\n",
            "Epoch 1761/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2748 - accuracy: 0.8667 - val_loss: 0.4985 - val_accuracy: 0.7714\n",
            "Epoch 1762/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2585 - accuracy: 0.8667 - val_loss: 0.4986 - val_accuracy: 0.7714\n",
            "Epoch 1763/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1869 - accuracy: 0.9667 - val_loss: 0.4979 - val_accuracy: 0.7714\n",
            "Epoch 1764/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3158 - accuracy: 0.9333 - val_loss: 0.4970 - val_accuracy: 0.7714\n",
            "Epoch 1765/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2365 - accuracy: 0.9000 - val_loss: 0.4960 - val_accuracy: 0.7714\n",
            "Epoch 1766/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2721 - accuracy: 0.9000 - val_loss: 0.4946 - val_accuracy: 0.7714\n",
            "Epoch 1767/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3408 - accuracy: 0.8000 - val_loss: 0.4945 - val_accuracy: 0.7714\n",
            "Epoch 1768/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3208 - accuracy: 0.8667 - val_loss: 0.4931 - val_accuracy: 0.7714\n",
            "Epoch 1769/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2777 - accuracy: 0.8667 - val_loss: 0.4930 - val_accuracy: 0.7714\n",
            "Epoch 1770/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1785 - accuracy: 0.9667 - val_loss: 0.4928 - val_accuracy: 0.7714\n",
            "Epoch 1771/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3428 - accuracy: 0.8333 - val_loss: 0.4914 - val_accuracy: 0.7714\n",
            "Epoch 1772/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2584 - accuracy: 0.8667 - val_loss: 0.4893 - val_accuracy: 0.7714\n",
            "Epoch 1773/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2408 - accuracy: 0.9333 - val_loss: 0.4880 - val_accuracy: 0.7714\n",
            "Epoch 1774/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2301 - accuracy: 0.9000 - val_loss: 0.4877 - val_accuracy: 0.7714\n",
            "Epoch 1775/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3028 - accuracy: 0.9000 - val_loss: 0.4868 - val_accuracy: 0.7714\n",
            "Epoch 1776/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2997 - accuracy: 0.8333 - val_loss: 0.4859 - val_accuracy: 0.7714\n",
            "Epoch 1777/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2716 - accuracy: 0.9000 - val_loss: 0.4848 - val_accuracy: 0.7714\n",
            "Epoch 1778/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2676 - accuracy: 0.9000 - val_loss: 0.4834 - val_accuracy: 0.7714\n",
            "Epoch 1779/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3230 - accuracy: 0.8333 - val_loss: 0.4827 - val_accuracy: 0.7714\n",
            "Epoch 1780/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2671 - accuracy: 0.8333 - val_loss: 0.4809 - val_accuracy: 0.7714\n",
            "Epoch 1781/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2994 - accuracy: 0.9333 - val_loss: 0.4802 - val_accuracy: 0.7714\n",
            "Epoch 1782/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2105 - accuracy: 0.9667 - val_loss: 0.4798 - val_accuracy: 0.7714\n",
            "Epoch 1783/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2269 - accuracy: 0.9333 - val_loss: 0.4796 - val_accuracy: 0.7714\n",
            "Epoch 1784/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2326 - accuracy: 0.9000 - val_loss: 0.4793 - val_accuracy: 0.7714\n",
            "Epoch 1785/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2369 - accuracy: 0.9333 - val_loss: 0.4789 - val_accuracy: 0.7714\n",
            "Epoch 1786/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2421 - accuracy: 0.9333 - val_loss: 0.4785 - val_accuracy: 0.7714\n",
            "Epoch 1787/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2609 - accuracy: 0.9000 - val_loss: 0.4783 - val_accuracy: 0.7714\n",
            "Epoch 1788/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3159 - accuracy: 0.8667 - val_loss: 0.4783 - val_accuracy: 0.7714\n",
            "Epoch 1789/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2610 - accuracy: 0.9000 - val_loss: 0.4790 - val_accuracy: 0.7714\n",
            "Epoch 1790/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.3050 - accuracy: 0.9000 - val_loss: 0.4799 - val_accuracy: 0.7714\n",
            "Epoch 1791/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2675 - accuracy: 0.9000 - val_loss: 0.4811 - val_accuracy: 0.7714\n",
            "Epoch 1792/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.2437 - accuracy: 0.8333 - val_loss: 0.4824 - val_accuracy: 0.7714\n",
            "Epoch 1793/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2495 - accuracy: 0.9000 - val_loss: 0.4839 - val_accuracy: 0.7714\n",
            "Epoch 1794/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2546 - accuracy: 0.9000 - val_loss: 0.4845 - val_accuracy: 0.7714\n",
            "Epoch 1795/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2092 - accuracy: 0.9000 - val_loss: 0.4848 - val_accuracy: 0.7714\n",
            "Epoch 1796/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2963 - accuracy: 0.8667 - val_loss: 0.4855 - val_accuracy: 0.7714\n",
            "Epoch 1797/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2123 - accuracy: 0.9667 - val_loss: 0.4868 - val_accuracy: 0.7714\n",
            "Epoch 1798/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2453 - accuracy: 0.9000 - val_loss: 0.4890 - val_accuracy: 0.7714\n",
            "Epoch 1799/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2166 - accuracy: 0.9333 - val_loss: 0.4908 - val_accuracy: 0.7571\n",
            "Epoch 1800/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2038 - accuracy: 0.9333 - val_loss: 0.4919 - val_accuracy: 0.7571\n",
            "Epoch 1801/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2995 - accuracy: 0.8667 - val_loss: 0.4926 - val_accuracy: 0.7571\n",
            "Epoch 1802/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2084 - accuracy: 1.0000 - val_loss: 0.4937 - val_accuracy: 0.7571\n",
            "Epoch 1803/4000\n",
            "1/1 [==============================] - 0s 210ms/step - loss: 0.2395 - accuracy: 0.9333 - val_loss: 0.4936 - val_accuracy: 0.7571\n",
            "Epoch 1804/4000\n",
            "1/1 [==============================] - 0s 107ms/step - loss: 0.2182 - accuracy: 0.9333 - val_loss: 0.4941 - val_accuracy: 0.7571\n",
            "Epoch 1805/4000\n",
            "1/1 [==============================] - 0s 101ms/step - loss: 0.3173 - accuracy: 0.9000 - val_loss: 0.4943 - val_accuracy: 0.7571\n",
            "Epoch 1806/4000\n",
            "1/1 [==============================] - 0s 155ms/step - loss: 0.3441 - accuracy: 0.9000 - val_loss: 0.4946 - val_accuracy: 0.7571\n",
            "Epoch 1807/4000\n",
            "1/1 [==============================] - 0s 214ms/step - loss: 0.2509 - accuracy: 0.9333 - val_loss: 0.4957 - val_accuracy: 0.7429\n",
            "Epoch 1808/4000\n",
            "1/1 [==============================] - 0s 199ms/step - loss: 0.3063 - accuracy: 0.8667 - val_loss: 0.4963 - val_accuracy: 0.7429\n",
            "Epoch 1809/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.3068 - accuracy: 0.9333 - val_loss: 0.4964 - val_accuracy: 0.7429\n",
            "Epoch 1810/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2631 - accuracy: 0.9333 - val_loss: 0.4964 - val_accuracy: 0.7429\n",
            "Epoch 1811/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.3193 - accuracy: 0.8667 - val_loss: 0.4965 - val_accuracy: 0.7429\n",
            "Epoch 1812/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2427 - accuracy: 0.9000 - val_loss: 0.4968 - val_accuracy: 0.7429\n",
            "Epoch 1813/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2216 - accuracy: 0.9333 - val_loss: 0.4963 - val_accuracy: 0.7429\n",
            "Epoch 1814/4000\n",
            "1/1 [==============================] - 0s 133ms/step - loss: 0.3477 - accuracy: 0.8333 - val_loss: 0.4965 - val_accuracy: 0.7429\n",
            "Epoch 1815/4000\n",
            "1/1 [==============================] - 0s 230ms/step - loss: 0.2712 - accuracy: 0.8667 - val_loss: 0.4965 - val_accuracy: 0.7429\n",
            "Epoch 1816/4000\n",
            "1/1 [==============================] - 0s 191ms/step - loss: 0.2553 - accuracy: 0.9333 - val_loss: 0.4977 - val_accuracy: 0.7429\n",
            "Epoch 1817/4000\n",
            "1/1 [==============================] - 0s 242ms/step - loss: 0.2078 - accuracy: 0.9333 - val_loss: 0.4989 - val_accuracy: 0.7429\n",
            "Epoch 1818/4000\n",
            "1/1 [==============================] - 0s 163ms/step - loss: 0.2601 - accuracy: 0.9333 - val_loss: 0.5002 - val_accuracy: 0.7429\n",
            "Epoch 1819/4000\n",
            "1/1 [==============================] - 0s 90ms/step - loss: 0.3737 - accuracy: 0.9000 - val_loss: 0.5003 - val_accuracy: 0.7429\n",
            "Epoch 1820/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2481 - accuracy: 0.9000 - val_loss: 0.5017 - val_accuracy: 0.7429\n",
            "Epoch 1821/4000\n",
            "1/1 [==============================] - 0s 225ms/step - loss: 0.3447 - accuracy: 0.8333 - val_loss: 0.5022 - val_accuracy: 0.7571\n",
            "Epoch 1822/4000\n",
            "1/1 [==============================] - 0s 274ms/step - loss: 0.2772 - accuracy: 0.8667 - val_loss: 0.5027 - val_accuracy: 0.7571\n",
            "Epoch 1823/4000\n",
            "1/1 [==============================] - 0s 203ms/step - loss: 0.3031 - accuracy: 0.9333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 1824/4000\n",
            "1/1 [==============================] - 0s 265ms/step - loss: 0.2887 - accuracy: 0.9333 - val_loss: 0.5008 - val_accuracy: 0.7571\n",
            "Epoch 1825/4000\n",
            "1/1 [==============================] - 0s 255ms/step - loss: 0.2589 - accuracy: 0.9000 - val_loss: 0.5001 - val_accuracy: 0.7714\n",
            "Epoch 1826/4000\n",
            "1/1 [==============================] - 0s 229ms/step - loss: 0.2905 - accuracy: 0.8667 - val_loss: 0.4991 - val_accuracy: 0.7714\n",
            "Epoch 1827/4000\n",
            "1/1 [==============================] - 0s 283ms/step - loss: 0.2827 - accuracy: 0.8667 - val_loss: 0.4989 - val_accuracy: 0.7714\n",
            "Epoch 1828/4000\n",
            "1/1 [==============================] - 0s 231ms/step - loss: 0.2472 - accuracy: 0.9000 - val_loss: 0.5000 - val_accuracy: 0.7714\n",
            "Epoch 1829/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3048 - accuracy: 0.9000 - val_loss: 0.5007 - val_accuracy: 0.7714\n",
            "Epoch 1830/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2535 - accuracy: 0.9667 - val_loss: 0.5007 - val_accuracy: 0.7714\n",
            "Epoch 1831/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2340 - accuracy: 0.9000 - val_loss: 0.5002 - val_accuracy: 0.7714\n",
            "Epoch 1832/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2138 - accuracy: 0.9333 - val_loss: 0.4995 - val_accuracy: 0.7714\n",
            "Epoch 1833/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2058 - accuracy: 0.9667 - val_loss: 0.4980 - val_accuracy: 0.7714\n",
            "Epoch 1834/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1982 - accuracy: 1.0000 - val_loss: 0.4964 - val_accuracy: 0.7714\n",
            "Epoch 1835/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3303 - accuracy: 0.9333 - val_loss: 0.4945 - val_accuracy: 0.7714\n",
            "Epoch 1836/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2301 - accuracy: 0.9667 - val_loss: 0.4931 - val_accuracy: 0.7714\n",
            "Epoch 1837/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2684 - accuracy: 0.9000 - val_loss: 0.4922 - val_accuracy: 0.7714\n",
            "Epoch 1838/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2551 - accuracy: 0.8667 - val_loss: 0.4922 - val_accuracy: 0.7714\n",
            "Epoch 1839/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2331 - accuracy: 0.8667 - val_loss: 0.4923 - val_accuracy: 0.7714\n",
            "Epoch 1840/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2421 - accuracy: 0.8667 - val_loss: 0.4918 - val_accuracy: 0.7714\n",
            "Epoch 1841/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2260 - accuracy: 0.9000 - val_loss: 0.4914 - val_accuracy: 0.7714\n",
            "Epoch 1842/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2877 - accuracy: 0.8667 - val_loss: 0.4919 - val_accuracy: 0.7714\n",
            "Epoch 1843/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2601 - accuracy: 0.9333 - val_loss: 0.4929 - val_accuracy: 0.7714\n",
            "Epoch 1844/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2304 - accuracy: 0.9000 - val_loss: 0.4944 - val_accuracy: 0.7714\n",
            "Epoch 1845/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2488 - accuracy: 0.9000 - val_loss: 0.4968 - val_accuracy: 0.7714\n",
            "Epoch 1846/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2795 - accuracy: 0.9000 - val_loss: 0.4984 - val_accuracy: 0.7714\n",
            "Epoch 1847/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2164 - accuracy: 0.9000 - val_loss: 0.4993 - val_accuracy: 0.7714\n",
            "Epoch 1848/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2142 - accuracy: 0.9000 - val_loss: 0.4995 - val_accuracy: 0.7714\n",
            "Epoch 1849/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2803 - accuracy: 0.9333 - val_loss: 0.4999 - val_accuracy: 0.7714\n",
            "Epoch 1850/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2410 - accuracy: 0.8667 - val_loss: 0.5012 - val_accuracy: 0.7714\n",
            "Epoch 1851/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2134 - accuracy: 0.9667 - val_loss: 0.5029 - val_accuracy: 0.7571\n",
            "Epoch 1852/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2536 - accuracy: 0.8667 - val_loss: 0.5043 - val_accuracy: 0.7571\n",
            "Epoch 1853/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2230 - accuracy: 0.9000 - val_loss: 0.5044 - val_accuracy: 0.7571\n",
            "Epoch 1854/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2587 - accuracy: 0.9333 - val_loss: 0.5037 - val_accuracy: 0.7571\n",
            "Epoch 1855/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1810 - accuracy: 0.9333 - val_loss: 0.5024 - val_accuracy: 0.7571\n",
            "Epoch 1856/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2513 - accuracy: 0.9333 - val_loss: 0.5021 - val_accuracy: 0.7571\n",
            "Epoch 1857/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3079 - accuracy: 0.8667 - val_loss: 0.5008 - val_accuracy: 0.7571\n",
            "Epoch 1858/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2634 - accuracy: 0.9333 - val_loss: 0.4992 - val_accuracy: 0.7571\n",
            "Epoch 1859/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3379 - accuracy: 0.8333 - val_loss: 0.4979 - val_accuracy: 0.7714\n",
            "Epoch 1860/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2336 - accuracy: 0.9333 - val_loss: 0.4977 - val_accuracy: 0.7857\n",
            "Epoch 1861/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2527 - accuracy: 0.9000 - val_loss: 0.4969 - val_accuracy: 0.7857\n",
            "Epoch 1862/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3425 - accuracy: 0.8667 - val_loss: 0.4971 - val_accuracy: 0.7857\n",
            "Epoch 1863/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2719 - accuracy: 0.9000 - val_loss: 0.4968 - val_accuracy: 0.7857\n",
            "Epoch 1864/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2027 - accuracy: 0.9333 - val_loss: 0.4965 - val_accuracy: 0.7857\n",
            "Epoch 1865/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1688 - accuracy: 0.9667 - val_loss: 0.4965 - val_accuracy: 0.7857\n",
            "Epoch 1866/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2445 - accuracy: 0.8667 - val_loss: 0.4975 - val_accuracy: 0.7857\n",
            "Epoch 1867/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1898 - accuracy: 0.9000 - val_loss: 0.4981 - val_accuracy: 0.7857\n",
            "Epoch 1868/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2308 - accuracy: 0.9333 - val_loss: 0.4990 - val_accuracy: 0.7857\n",
            "Epoch 1869/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2910 - accuracy: 0.8667 - val_loss: 0.4991 - val_accuracy: 0.7857\n",
            "Epoch 1870/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2367 - accuracy: 0.8333 - val_loss: 0.4991 - val_accuracy: 0.7857\n",
            "Epoch 1871/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2484 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7857\n",
            "Epoch 1872/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2320 - accuracy: 0.9333 - val_loss: 0.4973 - val_accuracy: 0.7857\n",
            "Epoch 1873/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2357 - accuracy: 0.9000 - val_loss: 0.4961 - val_accuracy: 0.7857\n",
            "Epoch 1874/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2424 - accuracy: 0.9000 - val_loss: 0.4941 - val_accuracy: 0.7857\n",
            "Epoch 1875/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2726 - accuracy: 0.8667 - val_loss: 0.4932 - val_accuracy: 0.7857\n",
            "Epoch 1876/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2464 - accuracy: 0.9667 - val_loss: 0.4925 - val_accuracy: 0.7857\n",
            "Epoch 1877/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2792 - accuracy: 0.9000 - val_loss: 0.4920 - val_accuracy: 0.7857\n",
            "Epoch 1878/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2941 - accuracy: 0.8667 - val_loss: 0.4909 - val_accuracy: 0.7857\n",
            "Epoch 1879/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2522 - accuracy: 0.9333 - val_loss: 0.4915 - val_accuracy: 0.7857\n",
            "Epoch 1880/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2271 - accuracy: 0.9000 - val_loss: 0.4928 - val_accuracy: 0.7857\n",
            "Epoch 1881/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2505 - accuracy: 0.9333 - val_loss: 0.4940 - val_accuracy: 0.7857\n",
            "Epoch 1882/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3276 - accuracy: 0.8667 - val_loss: 0.4954 - val_accuracy: 0.7857\n",
            "Epoch 1883/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2181 - accuracy: 0.9000 - val_loss: 0.4982 - val_accuracy: 0.7857\n",
            "Epoch 1884/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2389 - accuracy: 0.9333 - val_loss: 0.5009 - val_accuracy: 0.7714\n",
            "Epoch 1885/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2457 - accuracy: 0.9333 - val_loss: 0.5024 - val_accuracy: 0.7714\n",
            "Epoch 1886/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2569 - accuracy: 0.9333 - val_loss: 0.5048 - val_accuracy: 0.7429\n",
            "Epoch 1887/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2841 - accuracy: 0.8333 - val_loss: 0.5063 - val_accuracy: 0.7429\n",
            "Epoch 1888/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2836 - accuracy: 0.9000 - val_loss: 0.5061 - val_accuracy: 0.7429\n",
            "Epoch 1889/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2047 - accuracy: 0.9333 - val_loss: 0.5052 - val_accuracy: 0.7429\n",
            "Epoch 1890/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2147 - accuracy: 0.9333 - val_loss: 0.5033 - val_accuracy: 0.7429\n",
            "Epoch 1891/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2763 - accuracy: 0.8667 - val_loss: 0.5030 - val_accuracy: 0.7429\n",
            "Epoch 1892/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2808 - accuracy: 0.8000 - val_loss: 0.5028 - val_accuracy: 0.7429\n",
            "Epoch 1893/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1926 - accuracy: 1.0000 - val_loss: 0.5033 - val_accuracy: 0.7429\n",
            "Epoch 1894/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2610 - accuracy: 0.9333 - val_loss: 0.5047 - val_accuracy: 0.7429\n",
            "Epoch 1895/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3070 - accuracy: 0.8667 - val_loss: 0.5062 - val_accuracy: 0.7429\n",
            "Epoch 1896/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.3114 - accuracy: 0.8333 - val_loss: 0.5058 - val_accuracy: 0.7429\n",
            "Epoch 1897/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2837 - accuracy: 0.9000 - val_loss: 0.5034 - val_accuracy: 0.7429\n",
            "Epoch 1898/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2771 - accuracy: 0.9000 - val_loss: 0.5023 - val_accuracy: 0.7429\n",
            "Epoch 1899/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2748 - accuracy: 0.8667 - val_loss: 0.5006 - val_accuracy: 0.7429\n",
            "Epoch 1900/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.2972 - accuracy: 0.8667 - val_loss: 0.4975 - val_accuracy: 0.7429\n",
            "Epoch 1901/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3104 - accuracy: 0.9000 - val_loss: 0.4936 - val_accuracy: 0.7571\n",
            "Epoch 1902/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2775 - accuracy: 0.9333 - val_loss: 0.4897 - val_accuracy: 0.7714\n",
            "Epoch 1903/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2671 - accuracy: 0.9333 - val_loss: 0.4866 - val_accuracy: 0.7714\n",
            "Epoch 1904/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2844 - accuracy: 0.8667 - val_loss: 0.4841 - val_accuracy: 0.7714\n",
            "Epoch 1905/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.3108 - accuracy: 0.8333 - val_loss: 0.4826 - val_accuracy: 0.7714\n",
            "Epoch 1906/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2610 - accuracy: 0.9000 - val_loss: 0.4817 - val_accuracy: 0.7714\n",
            "Epoch 1907/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2106 - accuracy: 0.9667 - val_loss: 0.4807 - val_accuracy: 0.7714\n",
            "Epoch 1908/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.3150 - accuracy: 0.8333 - val_loss: 0.4798 - val_accuracy: 0.7714\n",
            "Epoch 1909/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2338 - accuracy: 0.9333 - val_loss: 0.4802 - val_accuracy: 0.7714\n",
            "Epoch 1910/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2293 - accuracy: 0.9333 - val_loss: 0.4806 - val_accuracy: 0.7714\n",
            "Epoch 1911/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2209 - accuracy: 0.9000 - val_loss: 0.4805 - val_accuracy: 0.7714\n",
            "Epoch 1912/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.3245 - accuracy: 0.9333 - val_loss: 0.4803 - val_accuracy: 0.7714\n",
            "Epoch 1913/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2760 - accuracy: 0.8667 - val_loss: 0.4808 - val_accuracy: 0.7714\n",
            "Epoch 1914/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2863 - accuracy: 0.8667 - val_loss: 0.4804 - val_accuracy: 0.7714\n",
            "Epoch 1915/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2811 - accuracy: 0.8667 - val_loss: 0.4804 - val_accuracy: 0.7714\n",
            "Epoch 1916/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.3619 - accuracy: 0.8667 - val_loss: 0.4805 - val_accuracy: 0.7714\n",
            "Epoch 1917/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.2465 - accuracy: 0.9000 - val_loss: 0.4821 - val_accuracy: 0.7714\n",
            "Epoch 1918/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3021 - accuracy: 0.8667 - val_loss: 0.4835 - val_accuracy: 0.7714\n",
            "Epoch 1919/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2852 - accuracy: 0.8667 - val_loss: 0.4857 - val_accuracy: 0.7571\n",
            "Epoch 1920/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3563 - accuracy: 0.8667 - val_loss: 0.4873 - val_accuracy: 0.7571\n",
            "Epoch 1921/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2278 - accuracy: 0.9333 - val_loss: 0.4885 - val_accuracy: 0.7571\n",
            "Epoch 1922/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2313 - accuracy: 0.9000 - val_loss: 0.4903 - val_accuracy: 0.7571\n",
            "Epoch 1923/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2338 - accuracy: 0.9000 - val_loss: 0.4906 - val_accuracy: 0.7571\n",
            "Epoch 1924/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2493 - accuracy: 0.9000 - val_loss: 0.4906 - val_accuracy: 0.7571\n",
            "Epoch 1925/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2337 - accuracy: 0.9333 - val_loss: 0.4906 - val_accuracy: 0.7571\n",
            "Epoch 1926/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2541 - accuracy: 0.9000 - val_loss: 0.4900 - val_accuracy: 0.7571\n",
            "Epoch 1927/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2238 - accuracy: 0.8667 - val_loss: 0.4895 - val_accuracy: 0.7571\n",
            "Epoch 1928/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2736 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.7571\n",
            "Epoch 1929/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2300 - accuracy: 0.9000 - val_loss: 0.4895 - val_accuracy: 0.7571\n",
            "Epoch 1930/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2609 - accuracy: 0.9333 - val_loss: 0.4905 - val_accuracy: 0.7571\n",
            "Epoch 1931/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2112 - accuracy: 0.9000 - val_loss: 0.4915 - val_accuracy: 0.7714\n",
            "Epoch 1932/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2090 - accuracy: 0.9667 - val_loss: 0.4920 - val_accuracy: 0.7714\n",
            "Epoch 1933/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2891 - accuracy: 0.9000 - val_loss: 0.4923 - val_accuracy: 0.7714\n",
            "Epoch 1934/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2496 - accuracy: 0.9333 - val_loss: 0.4939 - val_accuracy: 0.7571\n",
            "Epoch 1935/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2507 - accuracy: 0.9333 - val_loss: 0.4945 - val_accuracy: 0.7571\n",
            "Epoch 1936/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.3229 - accuracy: 0.8333 - val_loss: 0.4950 - val_accuracy: 0.7571\n",
            "Epoch 1937/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2900 - accuracy: 0.8667 - val_loss: 0.4948 - val_accuracy: 0.7714\n",
            "Epoch 1938/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.3752 - accuracy: 0.8333 - val_loss: 0.4943 - val_accuracy: 0.7714\n",
            "Epoch 1939/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2570 - accuracy: 0.9000 - val_loss: 0.4943 - val_accuracy: 0.7714\n",
            "Epoch 1940/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2260 - accuracy: 0.8667 - val_loss: 0.4954 - val_accuracy: 0.7714\n",
            "Epoch 1941/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2536 - accuracy: 0.9333 - val_loss: 0.4963 - val_accuracy: 0.7714\n",
            "Epoch 1942/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3226 - accuracy: 0.8333 - val_loss: 0.4982 - val_accuracy: 0.7571\n",
            "Epoch 1943/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1951 - accuracy: 0.9000 - val_loss: 0.5006 - val_accuracy: 0.7429\n",
            "Epoch 1944/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1987 - accuracy: 0.9333 - val_loss: 0.5036 - val_accuracy: 0.7429\n",
            "Epoch 1945/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.3058 - accuracy: 0.9000 - val_loss: 0.5068 - val_accuracy: 0.7429\n",
            "Epoch 1946/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2241 - accuracy: 0.9000 - val_loss: 0.5082 - val_accuracy: 0.7429\n",
            "Epoch 1947/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2311 - accuracy: 0.9333 - val_loss: 0.5083 - val_accuracy: 0.7429\n",
            "Epoch 1948/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2677 - accuracy: 0.8667 - val_loss: 0.5093 - val_accuracy: 0.7429\n",
            "Epoch 1949/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3004 - accuracy: 0.8667 - val_loss: 0.5090 - val_accuracy: 0.7429\n",
            "Epoch 1950/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2380 - accuracy: 0.9667 - val_loss: 0.5078 - val_accuracy: 0.7429\n",
            "Epoch 1951/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1899 - accuracy: 0.9333 - val_loss: 0.5062 - val_accuracy: 0.7429\n",
            "Epoch 1952/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2371 - accuracy: 0.9333 - val_loss: 0.5057 - val_accuracy: 0.7429\n",
            "Epoch 1953/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.3632 - accuracy: 0.8333 - val_loss: 0.5029 - val_accuracy: 0.7429\n",
            "Epoch 1954/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2559 - accuracy: 0.9000 - val_loss: 0.4996 - val_accuracy: 0.7429\n",
            "Epoch 1955/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2241 - accuracy: 0.9333 - val_loss: 0.4957 - val_accuracy: 0.7429\n",
            "Epoch 1956/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2340 - accuracy: 0.9667 - val_loss: 0.4923 - val_accuracy: 0.7429\n",
            "Epoch 1957/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2148 - accuracy: 0.9000 - val_loss: 0.4884 - val_accuracy: 0.7714\n",
            "Epoch 1958/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2764 - accuracy: 0.8667 - val_loss: 0.4847 - val_accuracy: 0.7857\n",
            "Epoch 1959/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2151 - accuracy: 0.9000 - val_loss: 0.4822 - val_accuracy: 0.7857\n",
            "Epoch 1960/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2082 - accuracy: 0.9000 - val_loss: 0.4803 - val_accuracy: 0.7857\n",
            "Epoch 1961/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2719 - accuracy: 0.9333 - val_loss: 0.4781 - val_accuracy: 0.7857\n",
            "Epoch 1962/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2289 - accuracy: 0.9000 - val_loss: 0.4763 - val_accuracy: 0.7857\n",
            "Epoch 1963/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2603 - accuracy: 0.9000 - val_loss: 0.4750 - val_accuracy: 0.7857\n",
            "Epoch 1964/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2753 - accuracy: 0.8667 - val_loss: 0.4749 - val_accuracy: 0.7857\n",
            "Epoch 1965/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3234 - accuracy: 0.8333 - val_loss: 0.4752 - val_accuracy: 0.7714\n",
            "Epoch 1966/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2291 - accuracy: 0.9667 - val_loss: 0.4764 - val_accuracy: 0.7714\n",
            "Epoch 1967/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3436 - accuracy: 0.8667 - val_loss: 0.4769 - val_accuracy: 0.7714\n",
            "Epoch 1968/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2225 - accuracy: 0.9000 - val_loss: 0.4781 - val_accuracy: 0.7714\n",
            "Epoch 1969/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2172 - accuracy: 0.9000 - val_loss: 0.4786 - val_accuracy: 0.7857\n",
            "Epoch 1970/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2665 - accuracy: 0.9000 - val_loss: 0.4789 - val_accuracy: 0.7857\n",
            "Epoch 1971/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2343 - accuracy: 0.9000 - val_loss: 0.4782 - val_accuracy: 0.7714\n",
            "Epoch 1972/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2387 - accuracy: 0.9333 - val_loss: 0.4783 - val_accuracy: 0.7714\n",
            "Epoch 1973/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2829 - accuracy: 0.9000 - val_loss: 0.4779 - val_accuracy: 0.7714\n",
            "Epoch 1974/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3130 - accuracy: 0.8667 - val_loss: 0.4782 - val_accuracy: 0.7714\n",
            "Epoch 1975/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2431 - accuracy: 0.9333 - val_loss: 0.4794 - val_accuracy: 0.7714\n",
            "Epoch 1976/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2577 - accuracy: 0.8667 - val_loss: 0.4807 - val_accuracy: 0.7714\n",
            "Epoch 1977/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2812 - accuracy: 0.9000 - val_loss: 0.4820 - val_accuracy: 0.7714\n",
            "Epoch 1978/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2759 - accuracy: 0.9000 - val_loss: 0.4827 - val_accuracy: 0.7714\n",
            "Epoch 1979/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2203 - accuracy: 0.9000 - val_loss: 0.4829 - val_accuracy: 0.7714\n",
            "Epoch 1980/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3056 - accuracy: 0.8333 - val_loss: 0.4856 - val_accuracy: 0.7714\n",
            "Epoch 1981/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2032 - accuracy: 1.0000 - val_loss: 0.4891 - val_accuracy: 0.7714\n",
            "Epoch 1982/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1908 - accuracy: 0.9667 - val_loss: 0.4925 - val_accuracy: 0.7571\n",
            "Epoch 1983/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2521 - accuracy: 0.9333 - val_loss: 0.4956 - val_accuracy: 0.7571\n",
            "Epoch 1984/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1939 - accuracy: 0.9333 - val_loss: 0.4989 - val_accuracy: 0.7571\n",
            "Epoch 1985/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2064 - accuracy: 0.9333 - val_loss: 0.5013 - val_accuracy: 0.7429\n",
            "Epoch 1986/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2560 - accuracy: 0.8333 - val_loss: 0.5041 - val_accuracy: 0.7429\n",
            "Epoch 1987/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2946 - accuracy: 0.9000 - val_loss: 0.5070 - val_accuracy: 0.7429\n",
            "Epoch 1988/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2872 - accuracy: 0.9000 - val_loss: 0.5099 - val_accuracy: 0.7429\n",
            "Epoch 1989/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2685 - accuracy: 0.9000 - val_loss: 0.5110 - val_accuracy: 0.7429\n",
            "Epoch 1990/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1416 - accuracy: 0.9667 - val_loss: 0.5133 - val_accuracy: 0.7429\n",
            "Epoch 1991/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2848 - accuracy: 0.9000 - val_loss: 0.5139 - val_accuracy: 0.7429\n",
            "Epoch 1992/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2554 - accuracy: 0.9000 - val_loss: 0.5144 - val_accuracy: 0.7429\n",
            "Epoch 1993/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1970 - accuracy: 1.0000 - val_loss: 0.5160 - val_accuracy: 0.7429\n",
            "Epoch 1994/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2039 - accuracy: 0.9667 - val_loss: 0.5173 - val_accuracy: 0.7429\n",
            "Epoch 1995/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2978 - accuracy: 0.9000 - val_loss: 0.5184 - val_accuracy: 0.7429\n",
            "Epoch 1996/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2516 - accuracy: 0.9000 - val_loss: 0.5186 - val_accuracy: 0.7429\n",
            "Epoch 1997/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1774 - accuracy: 0.9667 - val_loss: 0.5189 - val_accuracy: 0.7429\n",
            "Epoch 1998/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3149 - accuracy: 0.9000 - val_loss: 0.5186 - val_accuracy: 0.7571\n",
            "Epoch 1999/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3681 - accuracy: 0.8000 - val_loss: 0.5158 - val_accuracy: 0.7571\n",
            "Epoch 2000/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2646 - accuracy: 0.9000 - val_loss: 0.5119 - val_accuracy: 0.7571\n",
            "Epoch 2001/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2924 - accuracy: 0.9000 - val_loss: 0.5073 - val_accuracy: 0.7571\n",
            "Epoch 2002/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2281 - accuracy: 0.8667 - val_loss: 0.5034 - val_accuracy: 0.7571\n",
            "Epoch 2003/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.2945 - accuracy: 0.8667 - val_loss: 0.4984 - val_accuracy: 0.7571\n",
            "Epoch 2004/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2803 - accuracy: 0.8667 - val_loss: 0.4939 - val_accuracy: 0.7714\n",
            "Epoch 2005/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2813 - accuracy: 0.9000 - val_loss: 0.4894 - val_accuracy: 0.7714\n",
            "Epoch 2006/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2591 - accuracy: 0.9333 - val_loss: 0.4864 - val_accuracy: 0.7714\n",
            "Epoch 2007/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2784 - accuracy: 0.9333 - val_loss: 0.4841 - val_accuracy: 0.7714\n",
            "Epoch 2008/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2258 - accuracy: 0.9667 - val_loss: 0.4836 - val_accuracy: 0.7714\n",
            "Epoch 2009/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2527 - accuracy: 0.9000 - val_loss: 0.4832 - val_accuracy: 0.7714\n",
            "Epoch 2010/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2579 - accuracy: 0.9000 - val_loss: 0.4837 - val_accuracy: 0.7714\n",
            "Epoch 2011/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2058 - accuracy: 0.9333 - val_loss: 0.4850 - val_accuracy: 0.7714\n",
            "Epoch 2012/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2797 - accuracy: 0.9000 - val_loss: 0.4862 - val_accuracy: 0.7714\n",
            "Epoch 2013/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2435 - accuracy: 0.9333 - val_loss: 0.4879 - val_accuracy: 0.7714\n",
            "Epoch 2014/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2459 - accuracy: 0.9333 - val_loss: 0.4888 - val_accuracy: 0.7857\n",
            "Epoch 2015/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3308 - accuracy: 0.9000 - val_loss: 0.4905 - val_accuracy: 0.7857\n",
            "Epoch 2016/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1905 - accuracy: 0.9333 - val_loss: 0.4921 - val_accuracy: 0.7857\n",
            "Epoch 2017/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2705 - accuracy: 0.9000 - val_loss: 0.4936 - val_accuracy: 0.7714\n",
            "Epoch 2018/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2458 - accuracy: 0.9333 - val_loss: 0.4957 - val_accuracy: 0.7571\n",
            "Epoch 2019/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2784 - accuracy: 0.9333 - val_loss: 0.4986 - val_accuracy: 0.7571\n",
            "Epoch 2020/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.1936 - accuracy: 0.9667 - val_loss: 0.5024 - val_accuracy: 0.7571\n",
            "Epoch 2021/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2261 - accuracy: 0.9333 - val_loss: 0.5058 - val_accuracy: 0.7571\n",
            "Epoch 2022/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2882 - accuracy: 0.9000 - val_loss: 0.5090 - val_accuracy: 0.7571\n",
            "Epoch 2023/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2611 - accuracy: 0.9333 - val_loss: 0.5118 - val_accuracy: 0.7571\n",
            "Epoch 2024/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2810 - accuracy: 0.9000 - val_loss: 0.5143 - val_accuracy: 0.7429\n",
            "Epoch 2025/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3379 - accuracy: 0.8667 - val_loss: 0.5167 - val_accuracy: 0.7429\n",
            "Epoch 2026/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2540 - accuracy: 0.9000 - val_loss: 0.5176 - val_accuracy: 0.7429\n",
            "Epoch 2027/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2639 - accuracy: 0.9333 - val_loss: 0.5178 - val_accuracy: 0.7429\n",
            "Epoch 2028/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3202 - accuracy: 0.9000 - val_loss: 0.5191 - val_accuracy: 0.7286\n",
            "Epoch 2029/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2069 - accuracy: 0.9333 - val_loss: 0.5201 - val_accuracy: 0.7286\n",
            "Epoch 2030/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2953 - accuracy: 0.8333 - val_loss: 0.5217 - val_accuracy: 0.7286\n",
            "Epoch 2031/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2657 - accuracy: 0.9333 - val_loss: 0.5231 - val_accuracy: 0.7286\n",
            "Epoch 2032/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2330 - accuracy: 0.8667 - val_loss: 0.5245 - val_accuracy: 0.7286\n",
            "Epoch 2033/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2267 - accuracy: 0.9333 - val_loss: 0.5248 - val_accuracy: 0.7286\n",
            "Epoch 2034/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2379 - accuracy: 0.9667 - val_loss: 0.5243 - val_accuracy: 0.7286\n",
            "Epoch 2035/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2351 - accuracy: 0.9667 - val_loss: 0.5227 - val_accuracy: 0.7286\n",
            "Epoch 2036/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2618 - accuracy: 0.9000 - val_loss: 0.5195 - val_accuracy: 0.7429\n",
            "Epoch 2037/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2724 - accuracy: 0.9000 - val_loss: 0.5152 - val_accuracy: 0.7429\n",
            "Epoch 2038/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2717 - accuracy: 0.8333 - val_loss: 0.5100 - val_accuracy: 0.7429\n",
            "Epoch 2039/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2522 - accuracy: 0.9000 - val_loss: 0.5057 - val_accuracy: 0.7429\n",
            "Epoch 2040/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2251 - accuracy: 0.8667 - val_loss: 0.5026 - val_accuracy: 0.7429\n",
            "Epoch 2041/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2540 - accuracy: 0.9000 - val_loss: 0.4993 - val_accuracy: 0.7571\n",
            "Epoch 2042/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2602 - accuracy: 0.9000 - val_loss: 0.4960 - val_accuracy: 0.7571\n",
            "Epoch 2043/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1921 - accuracy: 0.9667 - val_loss: 0.4915 - val_accuracy: 0.7714\n",
            "Epoch 2044/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1961 - accuracy: 0.9333 - val_loss: 0.4882 - val_accuracy: 0.7857\n",
            "Epoch 2045/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.3086 - accuracy: 0.8667 - val_loss: 0.4834 - val_accuracy: 0.7857\n",
            "Epoch 2046/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2159 - accuracy: 0.9667 - val_loss: 0.4798 - val_accuracy: 0.7714\n",
            "Epoch 2047/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2064 - accuracy: 0.9333 - val_loss: 0.4766 - val_accuracy: 0.7714\n",
            "Epoch 2048/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2191 - accuracy: 0.9333 - val_loss: 0.4741 - val_accuracy: 0.7714\n",
            "Epoch 2049/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2698 - accuracy: 0.9333 - val_loss: 0.4726 - val_accuracy: 0.7714\n",
            "Epoch 2050/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2012 - accuracy: 0.9333 - val_loss: 0.4715 - val_accuracy: 0.7714\n",
            "Epoch 2051/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2011 - accuracy: 0.9333 - val_loss: 0.4712 - val_accuracy: 0.7714\n",
            "Epoch 2052/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2106 - accuracy: 0.9667 - val_loss: 0.4717 - val_accuracy: 0.7714\n",
            "Epoch 2053/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1904 - accuracy: 0.9667 - val_loss: 0.4738 - val_accuracy: 0.7714\n",
            "Epoch 2054/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2792 - accuracy: 0.9000 - val_loss: 0.4762 - val_accuracy: 0.7714\n",
            "Epoch 2055/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1660 - accuracy: 0.9667 - val_loss: 0.4795 - val_accuracy: 0.7714\n",
            "Epoch 2056/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3587 - accuracy: 0.9000 - val_loss: 0.4822 - val_accuracy: 0.7714\n",
            "Epoch 2057/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2584 - accuracy: 0.9000 - val_loss: 0.4832 - val_accuracy: 0.7714\n",
            "Epoch 2058/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1763 - accuracy: 0.9667 - val_loss: 0.4837 - val_accuracy: 0.7714\n",
            "Epoch 2059/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2771 - accuracy: 0.8333 - val_loss: 0.4840 - val_accuracy: 0.7571\n",
            "Epoch 2060/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3128 - accuracy: 0.8667 - val_loss: 0.4840 - val_accuracy: 0.7571\n",
            "Epoch 2061/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2730 - accuracy: 0.8667 - val_loss: 0.4845 - val_accuracy: 0.7714\n",
            "Epoch 2062/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1918 - accuracy: 0.9667 - val_loss: 0.4850 - val_accuracy: 0.7714\n",
            "Epoch 2063/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2165 - accuracy: 0.9333 - val_loss: 0.4859 - val_accuracy: 0.7571\n",
            "Epoch 2064/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3511 - accuracy: 0.7667 - val_loss: 0.4870 - val_accuracy: 0.7429\n",
            "Epoch 2065/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3090 - accuracy: 0.9000 - val_loss: 0.4866 - val_accuracy: 0.7429\n",
            "Epoch 2066/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2618 - accuracy: 0.8667 - val_loss: 0.4874 - val_accuracy: 0.7429\n",
            "Epoch 2067/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.1777 - accuracy: 0.9667 - val_loss: 0.4873 - val_accuracy: 0.7429\n",
            "Epoch 2068/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2159 - accuracy: 0.9667 - val_loss: 0.4876 - val_accuracy: 0.7429\n",
            "Epoch 2069/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2634 - accuracy: 0.9000 - val_loss: 0.4869 - val_accuracy: 0.7571\n",
            "Epoch 2070/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1982 - accuracy: 0.9333 - val_loss: 0.4859 - val_accuracy: 0.7571\n",
            "Epoch 2071/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1407 - accuracy: 1.0000 - val_loss: 0.4851 - val_accuracy: 0.7571\n",
            "Epoch 2072/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2757 - accuracy: 0.8667 - val_loss: 0.4842 - val_accuracy: 0.7571\n",
            "Epoch 2073/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2966 - accuracy: 0.8667 - val_loss: 0.4824 - val_accuracy: 0.7571\n",
            "Epoch 2074/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2610 - accuracy: 0.9000 - val_loss: 0.4803 - val_accuracy: 0.7571\n",
            "Epoch 2075/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.1934 - accuracy: 0.9667 - val_loss: 0.4780 - val_accuracy: 0.7714\n",
            "Epoch 2076/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2691 - accuracy: 0.9000 - val_loss: 0.4763 - val_accuracy: 0.7571\n",
            "Epoch 2077/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2275 - accuracy: 0.9000 - val_loss: 0.4747 - val_accuracy: 0.7571\n",
            "Epoch 2078/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2149 - accuracy: 0.9333 - val_loss: 0.4744 - val_accuracy: 0.7714\n",
            "Epoch 2079/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3551 - accuracy: 0.8000 - val_loss: 0.4736 - val_accuracy: 0.7714\n",
            "Epoch 2080/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2230 - accuracy: 0.8667 - val_loss: 0.4727 - val_accuracy: 0.7857\n",
            "Epoch 2081/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2357 - accuracy: 0.9000 - val_loss: 0.4726 - val_accuracy: 0.7857\n",
            "Epoch 2082/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1881 - accuracy: 0.9333 - val_loss: 0.4732 - val_accuracy: 0.7857\n",
            "Epoch 2083/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2789 - accuracy: 0.9333 - val_loss: 0.4731 - val_accuracy: 0.7857\n",
            "Epoch 2084/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.3059 - accuracy: 0.8667 - val_loss: 0.4739 - val_accuracy: 0.7857\n",
            "Epoch 2085/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2139 - accuracy: 0.9333 - val_loss: 0.4747 - val_accuracy: 0.7714\n",
            "Epoch 2086/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2608 - accuracy: 0.9000 - val_loss: 0.4768 - val_accuracy: 0.7714\n",
            "Epoch 2087/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2586 - accuracy: 0.9000 - val_loss: 0.4784 - val_accuracy: 0.7714\n",
            "Epoch 2088/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1933 - accuracy: 0.9667 - val_loss: 0.4794 - val_accuracy: 0.7714\n",
            "Epoch 2089/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2519 - accuracy: 0.8667 - val_loss: 0.4803 - val_accuracy: 0.7714\n",
            "Epoch 2090/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2300 - accuracy: 0.9000 - val_loss: 0.4820 - val_accuracy: 0.7571\n",
            "Epoch 2091/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1982 - accuracy: 0.9667 - val_loss: 0.4843 - val_accuracy: 0.7571\n",
            "Epoch 2092/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2185 - accuracy: 0.9667 - val_loss: 0.4870 - val_accuracy: 0.7571\n",
            "Epoch 2093/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2895 - accuracy: 0.8333 - val_loss: 0.4882 - val_accuracy: 0.7429\n",
            "Epoch 2094/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2213 - accuracy: 0.9667 - val_loss: 0.4884 - val_accuracy: 0.7429\n",
            "Epoch 2095/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2793 - accuracy: 0.8667 - val_loss: 0.4867 - val_accuracy: 0.7429\n",
            "Epoch 2096/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.3180 - accuracy: 0.8333 - val_loss: 0.4848 - val_accuracy: 0.7571\n",
            "Epoch 2097/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2481 - accuracy: 0.8333 - val_loss: 0.4836 - val_accuracy: 0.7571\n",
            "Epoch 2098/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2624 - accuracy: 0.8667 - val_loss: 0.4826 - val_accuracy: 0.7714\n",
            "Epoch 2099/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2022 - accuracy: 0.9333 - val_loss: 0.4818 - val_accuracy: 0.7714\n",
            "Epoch 2100/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2369 - accuracy: 0.9000 - val_loss: 0.4808 - val_accuracy: 0.7714\n",
            "Epoch 2101/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1872 - accuracy: 0.9333 - val_loss: 0.4791 - val_accuracy: 0.7857\n",
            "Epoch 2102/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2131 - accuracy: 0.9667 - val_loss: 0.4774 - val_accuracy: 0.7857\n",
            "Epoch 2103/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2175 - accuracy: 0.9333 - val_loss: 0.4765 - val_accuracy: 0.7857\n",
            "Epoch 2104/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2512 - accuracy: 0.8667 - val_loss: 0.4755 - val_accuracy: 0.7857\n",
            "Epoch 2105/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3238 - accuracy: 0.8333 - val_loss: 0.4748 - val_accuracy: 0.7857\n",
            "Epoch 2106/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2522 - accuracy: 0.9000 - val_loss: 0.4755 - val_accuracy: 0.7714\n",
            "Epoch 2107/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2222 - accuracy: 0.9333 - val_loss: 0.4758 - val_accuracy: 0.7714\n",
            "Epoch 2108/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2168 - accuracy: 0.9000 - val_loss: 0.4766 - val_accuracy: 0.7714\n",
            "Epoch 2109/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2785 - accuracy: 0.8667 - val_loss: 0.4780 - val_accuracy: 0.7714\n",
            "Epoch 2110/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2242 - accuracy: 0.9333 - val_loss: 0.4802 - val_accuracy: 0.7714\n",
            "Epoch 2111/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2653 - accuracy: 0.9000 - val_loss: 0.4819 - val_accuracy: 0.7714\n",
            "Epoch 2112/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1814 - accuracy: 0.9333 - val_loss: 0.4838 - val_accuracy: 0.7429\n",
            "Epoch 2113/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3104 - accuracy: 0.8333 - val_loss: 0.4874 - val_accuracy: 0.7571\n",
            "Epoch 2114/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2486 - accuracy: 0.9000 - val_loss: 0.4908 - val_accuracy: 0.7571\n",
            "Epoch 2115/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2375 - accuracy: 0.9333 - val_loss: 0.4932 - val_accuracy: 0.7571\n",
            "Epoch 2116/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2778 - accuracy: 0.8667 - val_loss: 0.4943 - val_accuracy: 0.7571\n",
            "Epoch 2117/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1785 - accuracy: 0.9667 - val_loss: 0.4944 - val_accuracy: 0.7571\n",
            "Epoch 2118/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2153 - accuracy: 0.9667 - val_loss: 0.4939 - val_accuracy: 0.7571\n",
            "Epoch 2119/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2357 - accuracy: 0.9333 - val_loss: 0.4937 - val_accuracy: 0.7429\n",
            "Epoch 2120/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1558 - accuracy: 0.9667 - val_loss: 0.4928 - val_accuracy: 0.7429\n",
            "Epoch 2121/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2446 - accuracy: 0.9333 - val_loss: 0.4916 - val_accuracy: 0.7429\n",
            "Epoch 2122/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3173 - accuracy: 0.8667 - val_loss: 0.4888 - val_accuracy: 0.7429\n",
            "Epoch 2123/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1784 - accuracy: 0.9333 - val_loss: 0.4869 - val_accuracy: 0.7429\n",
            "Epoch 2124/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2825 - accuracy: 0.9000 - val_loss: 0.4846 - val_accuracy: 0.7429\n",
            "Epoch 2125/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2043 - accuracy: 0.9667 - val_loss: 0.4826 - val_accuracy: 0.7714\n",
            "Epoch 2126/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2064 - accuracy: 0.9333 - val_loss: 0.4810 - val_accuracy: 0.7714\n",
            "Epoch 2127/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2292 - accuracy: 0.9333 - val_loss: 0.4803 - val_accuracy: 0.7714\n",
            "Epoch 2128/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2881 - accuracy: 0.9333 - val_loss: 0.4802 - val_accuracy: 0.7714\n",
            "Epoch 2129/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2666 - accuracy: 0.8667 - val_loss: 0.4816 - val_accuracy: 0.7714\n",
            "Epoch 2130/4000\n",
            "1/1 [==============================] - 0s 84ms/step - loss: 0.2376 - accuracy: 0.9333 - val_loss: 0.4823 - val_accuracy: 0.7714\n",
            "Epoch 2131/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1960 - accuracy: 0.9667 - val_loss: 0.4828 - val_accuracy: 0.7714\n",
            "Epoch 2132/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2822 - accuracy: 0.8667 - val_loss: 0.4836 - val_accuracy: 0.7714\n",
            "Epoch 2133/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3079 - accuracy: 0.8667 - val_loss: 0.4843 - val_accuracy: 0.7714\n",
            "Epoch 2134/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2786 - accuracy: 0.9000 - val_loss: 0.4847 - val_accuracy: 0.7714\n",
            "Epoch 2135/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2828 - accuracy: 0.9000 - val_loss: 0.4853 - val_accuracy: 0.7714\n",
            "Epoch 2136/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2424 - accuracy: 0.8667 - val_loss: 0.4859 - val_accuracy: 0.7714\n",
            "Epoch 2137/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2321 - accuracy: 0.9333 - val_loss: 0.4858 - val_accuracy: 0.7714\n",
            "Epoch 2138/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2650 - accuracy: 0.9333 - val_loss: 0.4856 - val_accuracy: 0.7714\n",
            "Epoch 2139/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1898 - accuracy: 0.9667 - val_loss: 0.4861 - val_accuracy: 0.7714\n",
            "Epoch 2140/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2296 - accuracy: 0.9333 - val_loss: 0.4877 - val_accuracy: 0.7714\n",
            "Epoch 2141/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2658 - accuracy: 0.9333 - val_loss: 0.4884 - val_accuracy: 0.7714\n",
            "Epoch 2142/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2601 - accuracy: 0.9000 - val_loss: 0.4891 - val_accuracy: 0.7714\n",
            "Epoch 2143/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.3271 - accuracy: 0.8333 - val_loss: 0.4899 - val_accuracy: 0.7714\n",
            "Epoch 2144/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2032 - accuracy: 0.9000 - val_loss: 0.4909 - val_accuracy: 0.7714\n",
            "Epoch 2145/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3436 - accuracy: 0.8333 - val_loss: 0.4913 - val_accuracy: 0.7714\n",
            "Epoch 2146/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2278 - accuracy: 0.9000 - val_loss: 0.4913 - val_accuracy: 0.7714\n",
            "Epoch 2147/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2870 - accuracy: 0.8667 - val_loss: 0.4903 - val_accuracy: 0.7714\n",
            "Epoch 2148/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2528 - accuracy: 0.9333 - val_loss: 0.4888 - val_accuracy: 0.7714\n",
            "Epoch 2149/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1701 - accuracy: 1.0000 - val_loss: 0.4885 - val_accuracy: 0.7714\n",
            "Epoch 2150/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2187 - accuracy: 0.9333 - val_loss: 0.4887 - val_accuracy: 0.7714\n",
            "Epoch 2151/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3112 - accuracy: 0.8333 - val_loss: 0.4894 - val_accuracy: 0.7714\n",
            "Epoch 2152/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2271 - accuracy: 0.9333 - val_loss: 0.4896 - val_accuracy: 0.7714\n",
            "Epoch 2153/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2630 - accuracy: 0.8667 - val_loss: 0.4907 - val_accuracy: 0.7714\n",
            "Epoch 2154/4000\n",
            "1/1 [==============================] - 0s 37ms/step - loss: 0.1359 - accuracy: 1.0000 - val_loss: 0.4915 - val_accuracy: 0.7714\n",
            "Epoch 2155/4000\n",
            "1/1 [==============================] - 0s 36ms/step - loss: 0.2501 - accuracy: 0.9000 - val_loss: 0.4912 - val_accuracy: 0.7714\n",
            "Epoch 2156/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2805 - accuracy: 0.9000 - val_loss: 0.4894 - val_accuracy: 0.7714\n",
            "Epoch 2157/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2101 - accuracy: 0.9667 - val_loss: 0.4883 - val_accuracy: 0.7714\n",
            "Epoch 2158/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.2117 - accuracy: 0.9333 - val_loss: 0.4868 - val_accuracy: 0.7714\n",
            "Epoch 2159/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2819 - accuracy: 0.8667 - val_loss: 0.4856 - val_accuracy: 0.7714\n",
            "Epoch 2160/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1750 - accuracy: 0.9667 - val_loss: 0.4842 - val_accuracy: 0.7714\n",
            "Epoch 2161/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2099 - accuracy: 0.9333 - val_loss: 0.4828 - val_accuracy: 0.7714\n",
            "Epoch 2162/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1779 - accuracy: 0.9667 - val_loss: 0.4815 - val_accuracy: 0.7857\n",
            "Epoch 2163/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.1910 - accuracy: 0.9667 - val_loss: 0.4796 - val_accuracy: 0.7857\n",
            "Epoch 2164/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1863 - accuracy: 0.9667 - val_loss: 0.4788 - val_accuracy: 0.7857\n",
            "Epoch 2165/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2695 - accuracy: 0.9000 - val_loss: 0.4770 - val_accuracy: 0.7857\n",
            "Epoch 2166/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2758 - accuracy: 0.8333 - val_loss: 0.4761 - val_accuracy: 0.7857\n",
            "Epoch 2167/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2437 - accuracy: 0.9000 - val_loss: 0.4747 - val_accuracy: 0.7714\n",
            "Epoch 2168/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2164 - accuracy: 0.9000 - val_loss: 0.4736 - val_accuracy: 0.7857\n",
            "Epoch 2169/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2133 - accuracy: 0.9333 - val_loss: 0.4736 - val_accuracy: 0.7714\n",
            "Epoch 2170/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2464 - accuracy: 0.9000 - val_loss: 0.4742 - val_accuracy: 0.7714\n",
            "Epoch 2171/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2338 - accuracy: 0.9333 - val_loss: 0.4746 - val_accuracy: 0.7714\n",
            "Epoch 2172/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1842 - accuracy: 0.9333 - val_loss: 0.4757 - val_accuracy: 0.7714\n",
            "Epoch 2173/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1977 - accuracy: 0.9333 - val_loss: 0.4774 - val_accuracy: 0.7714\n",
            "Epoch 2174/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1645 - accuracy: 0.9667 - val_loss: 0.4791 - val_accuracy: 0.7857\n",
            "Epoch 2175/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2098 - accuracy: 0.9333 - val_loss: 0.4810 - val_accuracy: 0.7857\n",
            "Epoch 2176/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2020 - accuracy: 1.0000 - val_loss: 0.4838 - val_accuracy: 0.7857\n",
            "Epoch 2177/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2805 - accuracy: 0.9000 - val_loss: 0.4850 - val_accuracy: 0.7857\n",
            "Epoch 2178/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3237 - accuracy: 0.8333 - val_loss: 0.4857 - val_accuracy: 0.7857\n",
            "Epoch 2179/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1875 - accuracy: 1.0000 - val_loss: 0.4862 - val_accuracy: 0.7857\n",
            "Epoch 2180/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2591 - accuracy: 0.8667 - val_loss: 0.4872 - val_accuracy: 0.7857\n",
            "Epoch 2181/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2672 - accuracy: 0.8667 - val_loss: 0.4894 - val_accuracy: 0.7857\n",
            "Epoch 2182/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2068 - accuracy: 0.9667 - val_loss: 0.4921 - val_accuracy: 0.7857\n",
            "Epoch 2183/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2621 - accuracy: 0.8667 - val_loss: 0.4934 - val_accuracy: 0.7857\n",
            "Epoch 2184/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2106 - accuracy: 0.9667 - val_loss: 0.4948 - val_accuracy: 0.7714\n",
            "Epoch 2185/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2632 - accuracy: 0.8667 - val_loss: 0.4966 - val_accuracy: 0.7714\n",
            "Epoch 2186/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2132 - accuracy: 0.9333 - val_loss: 0.4975 - val_accuracy: 0.7714\n",
            "Epoch 2187/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2484 - accuracy: 0.9000 - val_loss: 0.4975 - val_accuracy: 0.7571\n",
            "Epoch 2188/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1952 - accuracy: 0.9667 - val_loss: 0.4973 - val_accuracy: 0.7714\n",
            "Epoch 2189/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1710 - accuracy: 1.0000 - val_loss: 0.4971 - val_accuracy: 0.7714\n",
            "Epoch 2190/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1916 - accuracy: 0.9333 - val_loss: 0.4972 - val_accuracy: 0.7714\n",
            "Epoch 2191/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2441 - accuracy: 0.9333 - val_loss: 0.4979 - val_accuracy: 0.7714\n",
            "Epoch 2192/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2366 - accuracy: 0.9333 - val_loss: 0.4982 - val_accuracy: 0.7714\n",
            "Epoch 2193/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3069 - accuracy: 0.9000 - val_loss: 0.4967 - val_accuracy: 0.7857\n",
            "Epoch 2194/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2178 - accuracy: 0.9333 - val_loss: 0.4969 - val_accuracy: 0.7857\n",
            "Epoch 2195/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2700 - accuracy: 0.9000 - val_loss: 0.4965 - val_accuracy: 0.7857\n",
            "Epoch 2196/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1763 - accuracy: 0.9333 - val_loss: 0.4966 - val_accuracy: 0.7857\n",
            "Epoch 2197/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.3386 - accuracy: 0.9000 - val_loss: 0.4962 - val_accuracy: 0.7857\n",
            "Epoch 2198/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2379 - accuracy: 0.9667 - val_loss: 0.4954 - val_accuracy: 0.7857\n",
            "Epoch 2199/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2739 - accuracy: 0.9333 - val_loss: 0.4950 - val_accuracy: 0.7857\n",
            "Epoch 2200/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2920 - accuracy: 0.8667 - val_loss: 0.4941 - val_accuracy: 0.7857\n",
            "Epoch 2201/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1687 - accuracy: 0.9667 - val_loss: 0.4926 - val_accuracy: 0.7857\n",
            "Epoch 2202/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2857 - accuracy: 0.9000 - val_loss: 0.4905 - val_accuracy: 0.7857\n",
            "Epoch 2203/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2270 - accuracy: 0.9000 - val_loss: 0.4898 - val_accuracy: 0.7857\n",
            "Epoch 2204/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2015 - accuracy: 0.9000 - val_loss: 0.4895 - val_accuracy: 0.7857\n",
            "Epoch 2205/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1929 - accuracy: 0.9667 - val_loss: 0.4896 - val_accuracy: 0.7857\n",
            "Epoch 2206/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2160 - accuracy: 0.9000 - val_loss: 0.4894 - val_accuracy: 0.7857\n",
            "Epoch 2207/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3114 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.7714\n",
            "Epoch 2208/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2391 - accuracy: 0.9000 - val_loss: 0.4882 - val_accuracy: 0.7714\n",
            "Epoch 2209/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2240 - accuracy: 0.9000 - val_loss: 0.4873 - val_accuracy: 0.7714\n",
            "Epoch 2210/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2647 - accuracy: 0.9333 - val_loss: 0.4858 - val_accuracy: 0.7429\n",
            "Epoch 2211/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2741 - accuracy: 0.9000 - val_loss: 0.4854 - val_accuracy: 0.7571\n",
            "Epoch 2212/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2386 - accuracy: 0.9667 - val_loss: 0.4847 - val_accuracy: 0.7714\n",
            "Epoch 2213/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2391 - accuracy: 0.9000 - val_loss: 0.4837 - val_accuracy: 0.7714\n",
            "Epoch 2214/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2096 - accuracy: 0.9333 - val_loss: 0.4826 - val_accuracy: 0.7714\n",
            "Epoch 2215/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2787 - accuracy: 0.8333 - val_loss: 0.4815 - val_accuracy: 0.7714\n",
            "Epoch 2216/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2063 - accuracy: 0.9333 - val_loss: 0.4804 - val_accuracy: 0.7714\n",
            "Epoch 2217/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1933 - accuracy: 0.9667 - val_loss: 0.4800 - val_accuracy: 0.7857\n",
            "Epoch 2218/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1751 - accuracy: 0.9667 - val_loss: 0.4801 - val_accuracy: 0.7857\n",
            "Epoch 2219/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.3420 - accuracy: 0.8333 - val_loss: 0.4805 - val_accuracy: 0.7857\n",
            "Epoch 2220/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2046 - accuracy: 0.9333 - val_loss: 0.4813 - val_accuracy: 0.7857\n",
            "Epoch 2221/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.3099 - accuracy: 0.9000 - val_loss: 0.4817 - val_accuracy: 0.7857\n",
            "Epoch 2222/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2053 - accuracy: 0.9333 - val_loss: 0.4814 - val_accuracy: 0.7857\n",
            "Epoch 2223/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1996 - accuracy: 0.9000 - val_loss: 0.4821 - val_accuracy: 0.8000\n",
            "Epoch 2224/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2700 - accuracy: 0.9667 - val_loss: 0.4824 - val_accuracy: 0.8000\n",
            "Epoch 2225/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1838 - accuracy: 0.9667 - val_loss: 0.4828 - val_accuracy: 0.8000\n",
            "Epoch 2226/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1701 - accuracy: 0.9667 - val_loss: 0.4836 - val_accuracy: 0.8000\n",
            "Epoch 2227/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2432 - accuracy: 0.8667 - val_loss: 0.4841 - val_accuracy: 0.8000\n",
            "Epoch 2228/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2751 - accuracy: 0.8667 - val_loss: 0.4839 - val_accuracy: 0.8000\n",
            "Epoch 2229/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2079 - accuracy: 0.9333 - val_loss: 0.4845 - val_accuracy: 0.8000\n",
            "Epoch 2230/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.3051 - accuracy: 0.8333 - val_loss: 0.4852 - val_accuracy: 0.7857\n",
            "Epoch 2231/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2440 - accuracy: 0.9000 - val_loss: 0.4842 - val_accuracy: 0.7857\n",
            "Epoch 2232/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2022 - accuracy: 0.9000 - val_loss: 0.4827 - val_accuracy: 0.7857\n",
            "Epoch 2233/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.3137 - accuracy: 0.9000 - val_loss: 0.4806 - val_accuracy: 0.7857\n",
            "Epoch 2234/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2290 - accuracy: 0.8667 - val_loss: 0.4788 - val_accuracy: 0.7857\n",
            "Epoch 2235/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2417 - accuracy: 0.9000 - val_loss: 0.4773 - val_accuracy: 0.7857\n",
            "Epoch 2236/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1986 - accuracy: 0.9333 - val_loss: 0.4775 - val_accuracy: 0.7857\n",
            "Epoch 2237/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1559 - accuracy: 0.9667 - val_loss: 0.4774 - val_accuracy: 0.7857\n",
            "Epoch 2238/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2399 - accuracy: 0.8667 - val_loss: 0.4774 - val_accuracy: 0.7857\n",
            "Epoch 2239/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2390 - accuracy: 0.9000 - val_loss: 0.4777 - val_accuracy: 0.7857\n",
            "Epoch 2240/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2450 - accuracy: 0.9000 - val_loss: 0.4782 - val_accuracy: 0.7857\n",
            "Epoch 2241/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2814 - accuracy: 0.8667 - val_loss: 0.4800 - val_accuracy: 0.7857\n",
            "Epoch 2242/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2247 - accuracy: 0.9667 - val_loss: 0.4831 - val_accuracy: 0.7857\n",
            "Epoch 2243/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2331 - accuracy: 0.9333 - val_loss: 0.4858 - val_accuracy: 0.7857\n",
            "Epoch 2244/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2771 - accuracy: 0.9000 - val_loss: 0.4878 - val_accuracy: 0.7857\n",
            "Epoch 2245/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2097 - accuracy: 0.9667 - val_loss: 0.4895 - val_accuracy: 0.7714\n",
            "Epoch 2246/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2755 - accuracy: 0.9000 - val_loss: 0.4907 - val_accuracy: 0.7571\n",
            "Epoch 2247/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2048 - accuracy: 0.9667 - val_loss: 0.4912 - val_accuracy: 0.7571\n",
            "Epoch 2248/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2144 - accuracy: 0.9667 - val_loss: 0.4918 - val_accuracy: 0.7571\n",
            "Epoch 2249/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2383 - accuracy: 0.9333 - val_loss: 0.4920 - val_accuracy: 0.7571\n",
            "Epoch 2250/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2908 - accuracy: 0.8333 - val_loss: 0.4925 - val_accuracy: 0.7571\n",
            "Epoch 2251/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2115 - accuracy: 0.9000 - val_loss: 0.4924 - val_accuracy: 0.7571\n",
            "Epoch 2252/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2409 - accuracy: 0.9667 - val_loss: 0.4932 - val_accuracy: 0.7571\n",
            "Epoch 2253/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.3150 - accuracy: 0.8667 - val_loss: 0.4931 - val_accuracy: 0.7571\n",
            "Epoch 2254/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2208 - accuracy: 0.8667 - val_loss: 0.4927 - val_accuracy: 0.7571\n",
            "Epoch 2255/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2047 - accuracy: 0.9333 - val_loss: 0.4926 - val_accuracy: 0.7571\n",
            "Epoch 2256/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2504 - accuracy: 0.9000 - val_loss: 0.4913 - val_accuracy: 0.7714\n",
            "Epoch 2257/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2087 - accuracy: 0.9333 - val_loss: 0.4904 - val_accuracy: 0.7714\n",
            "Epoch 2258/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3219 - accuracy: 0.8000 - val_loss: 0.4893 - val_accuracy: 0.7714\n",
            "Epoch 2259/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2270 - accuracy: 0.9000 - val_loss: 0.4885 - val_accuracy: 0.7857\n",
            "Epoch 2260/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2218 - accuracy: 0.9667 - val_loss: 0.4881 - val_accuracy: 0.7857\n",
            "Epoch 2261/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1813 - accuracy: 1.0000 - val_loss: 0.4881 - val_accuracy: 0.7857\n",
            "Epoch 2262/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2322 - accuracy: 0.8667 - val_loss: 0.4893 - val_accuracy: 0.7857\n",
            "Epoch 2263/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2991 - accuracy: 0.8667 - val_loss: 0.4903 - val_accuracy: 0.7714\n",
            "Epoch 2264/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2932 - accuracy: 0.8667 - val_loss: 0.4915 - val_accuracy: 0.7714\n",
            "Epoch 2265/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2836 - accuracy: 0.8667 - val_loss: 0.4936 - val_accuracy: 0.7714\n",
            "Epoch 2266/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2421 - accuracy: 0.9333 - val_loss: 0.4949 - val_accuracy: 0.7714\n",
            "Epoch 2267/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2358 - accuracy: 0.9000 - val_loss: 0.4966 - val_accuracy: 0.7714\n",
            "Epoch 2268/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1841 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7714\n",
            "Epoch 2269/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2714 - accuracy: 0.9000 - val_loss: 0.5005 - val_accuracy: 0.7714\n",
            "Epoch 2270/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.3691 - accuracy: 0.8667 - val_loss: 0.5022 - val_accuracy: 0.7429\n",
            "Epoch 2271/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2017 - accuracy: 0.9333 - val_loss: 0.5037 - val_accuracy: 0.7429\n",
            "Epoch 2272/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2237 - accuracy: 0.9667 - val_loss: 0.5059 - val_accuracy: 0.7429\n",
            "Epoch 2273/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2730 - accuracy: 0.8667 - val_loss: 0.5087 - val_accuracy: 0.7429\n",
            "Epoch 2274/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2491 - accuracy: 0.9000 - val_loss: 0.5099 - val_accuracy: 0.7429\n",
            "Epoch 2275/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2421 - accuracy: 0.9000 - val_loss: 0.5093 - val_accuracy: 0.7429\n",
            "Epoch 2276/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2127 - accuracy: 0.9333 - val_loss: 0.5101 - val_accuracy: 0.7429\n",
            "Epoch 2277/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2300 - accuracy: 0.9667 - val_loss: 0.5104 - val_accuracy: 0.7429\n",
            "Epoch 2278/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1920 - accuracy: 0.9667 - val_loss: 0.5106 - val_accuracy: 0.7429\n",
            "Epoch 2279/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1685 - accuracy: 0.9667 - val_loss: 0.5108 - val_accuracy: 0.7429\n",
            "Epoch 2280/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2160 - accuracy: 0.9333 - val_loss: 0.5102 - val_accuracy: 0.7571\n",
            "Epoch 2281/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1481 - accuracy: 1.0000 - val_loss: 0.5101 - val_accuracy: 0.7571\n",
            "Epoch 2282/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2107 - accuracy: 0.9333 - val_loss: 0.5105 - val_accuracy: 0.7571\n",
            "Epoch 2283/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2268 - accuracy: 0.9667 - val_loss: 0.5107 - val_accuracy: 0.7571\n",
            "Epoch 2284/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2244 - accuracy: 0.8667 - val_loss: 0.5096 - val_accuracy: 0.7571\n",
            "Epoch 2285/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2142 - accuracy: 0.8667 - val_loss: 0.5086 - val_accuracy: 0.7571\n",
            "Epoch 2286/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1541 - accuracy: 0.9667 - val_loss: 0.5070 - val_accuracy: 0.7571\n",
            "Epoch 2287/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1726 - accuracy: 0.9667 - val_loss: 0.5049 - val_accuracy: 0.7571\n",
            "Epoch 2288/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2524 - accuracy: 0.9333 - val_loss: 0.5027 - val_accuracy: 0.7571\n",
            "Epoch 2289/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1891 - accuracy: 0.9333 - val_loss: 0.5003 - val_accuracy: 0.7571\n",
            "Epoch 2290/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2534 - accuracy: 0.9000 - val_loss: 0.4987 - val_accuracy: 0.7571\n",
            "Epoch 2291/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.1960 - accuracy: 1.0000 - val_loss: 0.4964 - val_accuracy: 0.7714\n",
            "Epoch 2292/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2606 - accuracy: 0.9333 - val_loss: 0.4946 - val_accuracy: 0.7714\n",
            "Epoch 2293/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2205 - accuracy: 0.8667 - val_loss: 0.4940 - val_accuracy: 0.7714\n",
            "Epoch 2294/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2760 - accuracy: 0.9000 - val_loss: 0.4921 - val_accuracy: 0.7857\n",
            "Epoch 2295/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2733 - accuracy: 0.9000 - val_loss: 0.4895 - val_accuracy: 0.7857\n",
            "Epoch 2296/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2298 - accuracy: 0.9000 - val_loss: 0.4870 - val_accuracy: 0.7714\n",
            "Epoch 2297/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1886 - accuracy: 0.9667 - val_loss: 0.4847 - val_accuracy: 0.7714\n",
            "Epoch 2298/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.3055 - accuracy: 0.8333 - val_loss: 0.4821 - val_accuracy: 0.7857\n",
            "Epoch 2299/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2215 - accuracy: 0.9000 - val_loss: 0.4810 - val_accuracy: 0.7857\n",
            "Epoch 2300/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2675 - accuracy: 0.9000 - val_loss: 0.4808 - val_accuracy: 0.7857\n",
            "Epoch 2301/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2671 - accuracy: 0.9000 - val_loss: 0.4813 - val_accuracy: 0.7857\n",
            "Epoch 2302/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2446 - accuracy: 0.8333 - val_loss: 0.4808 - val_accuracy: 0.7857\n",
            "Epoch 2303/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2084 - accuracy: 0.9333 - val_loss: 0.4800 - val_accuracy: 0.7857\n",
            "Epoch 2304/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2616 - accuracy: 0.8667 - val_loss: 0.4791 - val_accuracy: 0.7857\n",
            "Epoch 2305/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2369 - accuracy: 0.9000 - val_loss: 0.4788 - val_accuracy: 0.7857\n",
            "Epoch 2306/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1572 - accuracy: 0.9667 - val_loss: 0.4785 - val_accuracy: 0.7857\n",
            "Epoch 2307/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1959 - accuracy: 0.9333 - val_loss: 0.4780 - val_accuracy: 0.7857\n",
            "Epoch 2308/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2299 - accuracy: 0.9333 - val_loss: 0.4784 - val_accuracy: 0.7857\n",
            "Epoch 2309/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2813 - accuracy: 0.8667 - val_loss: 0.4772 - val_accuracy: 0.7857\n",
            "Epoch 2310/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2314 - accuracy: 0.9333 - val_loss: 0.4760 - val_accuracy: 0.7857\n",
            "Epoch 2311/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.3109 - accuracy: 0.8333 - val_loss: 0.4743 - val_accuracy: 0.7857\n",
            "Epoch 2312/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2009 - accuracy: 0.9333 - val_loss: 0.4731 - val_accuracy: 0.7857\n",
            "Epoch 2313/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2172 - accuracy: 0.8667 - val_loss: 0.4734 - val_accuracy: 0.7857\n",
            "Epoch 2314/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2746 - accuracy: 0.9000 - val_loss: 0.4733 - val_accuracy: 0.7857\n",
            "Epoch 2315/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2674 - accuracy: 0.9000 - val_loss: 0.4739 - val_accuracy: 0.7857\n",
            "Epoch 2316/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2172 - accuracy: 0.9000 - val_loss: 0.4757 - val_accuracy: 0.8000\n",
            "Epoch 2317/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2583 - accuracy: 0.8667 - val_loss: 0.4787 - val_accuracy: 0.8000\n",
            "Epoch 2318/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1816 - accuracy: 0.9333 - val_loss: 0.4822 - val_accuracy: 0.8000\n",
            "Epoch 2319/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2641 - accuracy: 0.8667 - val_loss: 0.4856 - val_accuracy: 0.7857\n",
            "Epoch 2320/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1698 - accuracy: 0.9667 - val_loss: 0.4887 - val_accuracy: 0.7714\n",
            "Epoch 2321/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2465 - accuracy: 0.8667 - val_loss: 0.4918 - val_accuracy: 0.7714\n",
            "Epoch 2322/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1447 - accuracy: 0.9667 - val_loss: 0.4952 - val_accuracy: 0.7714\n",
            "Epoch 2323/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1683 - accuracy: 0.9667 - val_loss: 0.4977 - val_accuracy: 0.7714\n",
            "Epoch 2324/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2523 - accuracy: 0.8667 - val_loss: 0.5013 - val_accuracy: 0.7714\n",
            "Epoch 2325/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2387 - accuracy: 0.9333 - val_loss: 0.5050 - val_accuracy: 0.7714\n",
            "Epoch 2326/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2440 - accuracy: 0.9333 - val_loss: 0.5096 - val_accuracy: 0.7714\n",
            "Epoch 2327/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2967 - accuracy: 0.8333 - val_loss: 0.5123 - val_accuracy: 0.7714\n",
            "Epoch 2328/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2610 - accuracy: 0.9333 - val_loss: 0.5160 - val_accuracy: 0.7571\n",
            "Epoch 2329/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2565 - accuracy: 0.8667 - val_loss: 0.5181 - val_accuracy: 0.7571\n",
            "Epoch 2330/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2485 - accuracy: 0.9333 - val_loss: 0.5192 - val_accuracy: 0.7571\n",
            "Epoch 2331/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2183 - accuracy: 0.9667 - val_loss: 0.5201 - val_accuracy: 0.7571\n",
            "Epoch 2332/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2942 - accuracy: 0.8667 - val_loss: 0.5201 - val_accuracy: 0.7571\n",
            "Epoch 2333/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2931 - accuracy: 0.9333 - val_loss: 0.5193 - val_accuracy: 0.7571\n",
            "Epoch 2334/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2433 - accuracy: 0.9000 - val_loss: 0.5174 - val_accuracy: 0.7571\n",
            "Epoch 2335/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2733 - accuracy: 0.8333 - val_loss: 0.5138 - val_accuracy: 0.7571\n",
            "Epoch 2336/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2493 - accuracy: 0.9000 - val_loss: 0.5083 - val_accuracy: 0.7714\n",
            "Epoch 2337/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1783 - accuracy: 0.9667 - val_loss: 0.5036 - val_accuracy: 0.7714\n",
            "Epoch 2338/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2199 - accuracy: 0.9000 - val_loss: 0.4995 - val_accuracy: 0.7714\n",
            "Epoch 2339/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1864 - accuracy: 0.9000 - val_loss: 0.4963 - val_accuracy: 0.7571\n",
            "Epoch 2340/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2462 - accuracy: 0.9333 - val_loss: 0.4929 - val_accuracy: 0.7571\n",
            "Epoch 2341/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.1777 - accuracy: 0.9333 - val_loss: 0.4898 - val_accuracy: 0.7571\n",
            "Epoch 2342/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2880 - accuracy: 0.9000 - val_loss: 0.4877 - val_accuracy: 0.7571\n",
            "Epoch 2343/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1975 - accuracy: 0.9667 - val_loss: 0.4876 - val_accuracy: 0.7571\n",
            "Epoch 2344/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1969 - accuracy: 0.9333 - val_loss: 0.4870 - val_accuracy: 0.7571\n",
            "Epoch 2345/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2338 - accuracy: 0.9667 - val_loss: 0.4869 - val_accuracy: 0.7571\n",
            "Epoch 2346/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2746 - accuracy: 0.9000 - val_loss: 0.4857 - val_accuracy: 0.7571\n",
            "Epoch 2347/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1673 - accuracy: 0.9333 - val_loss: 0.4844 - val_accuracy: 0.7571\n",
            "Epoch 2348/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2316 - accuracy: 0.9000 - val_loss: 0.4843 - val_accuracy: 0.7571\n",
            "Epoch 2349/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2625 - accuracy: 0.9333 - val_loss: 0.4837 - val_accuracy: 0.7571\n",
            "Epoch 2350/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.3029 - accuracy: 0.8333 - val_loss: 0.4835 - val_accuracy: 0.7571\n",
            "Epoch 2351/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2051 - accuracy: 0.9000 - val_loss: 0.4829 - val_accuracy: 0.7571\n",
            "Epoch 2352/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2123 - accuracy: 0.9333 - val_loss: 0.4817 - val_accuracy: 0.7571\n",
            "Epoch 2353/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1890 - accuracy: 0.9667 - val_loss: 0.4807 - val_accuracy: 0.7571\n",
            "Epoch 2354/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1898 - accuracy: 0.9333 - val_loss: 0.4797 - val_accuracy: 0.7571\n",
            "Epoch 2355/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2238 - accuracy: 0.9000 - val_loss: 0.4800 - val_accuracy: 0.7571\n",
            "Epoch 2356/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2114 - accuracy: 0.9667 - val_loss: 0.4798 - val_accuracy: 0.7571\n",
            "Epoch 2357/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2942 - accuracy: 0.9333 - val_loss: 0.4792 - val_accuracy: 0.7571\n",
            "Epoch 2358/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2815 - accuracy: 0.9000 - val_loss: 0.4805 - val_accuracy: 0.7571\n",
            "Epoch 2359/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2563 - accuracy: 0.9333 - val_loss: 0.4813 - val_accuracy: 0.7571\n",
            "Epoch 2360/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.1688 - accuracy: 0.9333 - val_loss: 0.4830 - val_accuracy: 0.7571\n",
            "Epoch 2361/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2951 - accuracy: 0.9000 - val_loss: 0.4835 - val_accuracy: 0.7571\n",
            "Epoch 2362/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.3087 - accuracy: 0.8333 - val_loss: 0.4838 - val_accuracy: 0.7571\n",
            "Epoch 2363/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2492 - accuracy: 0.9667 - val_loss: 0.4836 - val_accuracy: 0.7571\n",
            "Epoch 2364/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2673 - accuracy: 0.8667 - val_loss: 0.4838 - val_accuracy: 0.7571\n",
            "Epoch 2365/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2432 - accuracy: 0.8667 - val_loss: 0.4852 - val_accuracy: 0.7571\n",
            "Epoch 2366/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2798 - accuracy: 0.8667 - val_loss: 0.4857 - val_accuracy: 0.7571\n",
            "Epoch 2367/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2848 - accuracy: 0.8667 - val_loss: 0.4862 - val_accuracy: 0.7571\n",
            "Epoch 2368/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2198 - accuracy: 0.9667 - val_loss: 0.4874 - val_accuracy: 0.7714\n",
            "Epoch 2369/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.3453 - accuracy: 0.8333 - val_loss: 0.4893 - val_accuracy: 0.7714\n",
            "Epoch 2370/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1665 - accuracy: 1.0000 - val_loss: 0.4915 - val_accuracy: 0.7714\n",
            "Epoch 2371/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2639 - accuracy: 0.9000 - val_loss: 0.4937 - val_accuracy: 0.7571\n",
            "Epoch 2372/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3528 - accuracy: 0.8000 - val_loss: 0.4964 - val_accuracy: 0.7571\n",
            "Epoch 2373/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1582 - accuracy: 0.9667 - val_loss: 0.4991 - val_accuracy: 0.7571\n",
            "Epoch 2374/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1512 - accuracy: 1.0000 - val_loss: 0.5017 - val_accuracy: 0.7571\n",
            "Epoch 2375/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2127 - accuracy: 0.9333 - val_loss: 0.5034 - val_accuracy: 0.7571\n",
            "Epoch 2376/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2110 - accuracy: 0.9333 - val_loss: 0.5039 - val_accuracy: 0.7571\n",
            "Epoch 2377/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.3026 - accuracy: 0.8667 - val_loss: 0.5050 - val_accuracy: 0.7571\n",
            "Epoch 2378/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2668 - accuracy: 0.8000 - val_loss: 0.5060 - val_accuracy: 0.7571\n",
            "Epoch 2379/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2787 - accuracy: 0.9000 - val_loss: 0.5056 - val_accuracy: 0.7571\n",
            "Epoch 2380/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1945 - accuracy: 0.9333 - val_loss: 0.5063 - val_accuracy: 0.7571\n",
            "Epoch 2381/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3152 - accuracy: 0.7667 - val_loss: 0.5055 - val_accuracy: 0.7571\n",
            "Epoch 2382/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2123 - accuracy: 0.9000 - val_loss: 0.5051 - val_accuracy: 0.7571\n",
            "Epoch 2383/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1847 - accuracy: 0.9333 - val_loss: 0.5052 - val_accuracy: 0.7571\n",
            "Epoch 2384/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2568 - accuracy: 0.9333 - val_loss: 0.5062 - val_accuracy: 0.7571\n",
            "Epoch 2385/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2080 - accuracy: 0.9667 - val_loss: 0.5064 - val_accuracy: 0.7571\n",
            "Epoch 2386/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2317 - accuracy: 0.9000 - val_loss: 0.5073 - val_accuracy: 0.7571\n",
            "Epoch 2387/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2215 - accuracy: 0.9333 - val_loss: 0.5072 - val_accuracy: 0.7571\n",
            "Epoch 2388/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1974 - accuracy: 0.9333 - val_loss: 0.5049 - val_accuracy: 0.7571\n",
            "Epoch 2389/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2233 - accuracy: 0.9333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 2390/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1668 - accuracy: 0.9333 - val_loss: 0.4982 - val_accuracy: 0.7571\n",
            "Epoch 2391/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2726 - accuracy: 0.8333 - val_loss: 0.4945 - val_accuracy: 0.7714\n",
            "Epoch 2392/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2984 - accuracy: 0.8333 - val_loss: 0.4917 - val_accuracy: 0.7857\n",
            "Epoch 2393/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2459 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.7857\n",
            "Epoch 2394/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2799 - accuracy: 0.8667 - val_loss: 0.4864 - val_accuracy: 0.7857\n",
            "Epoch 2395/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2018 - accuracy: 0.9333 - val_loss: 0.4839 - val_accuracy: 0.7857\n",
            "Epoch 2396/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2575 - accuracy: 0.9000 - val_loss: 0.4808 - val_accuracy: 0.7857\n",
            "Epoch 2397/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2782 - accuracy: 0.9000 - val_loss: 0.4805 - val_accuracy: 0.8000\n",
            "Epoch 2398/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2571 - accuracy: 0.9000 - val_loss: 0.4805 - val_accuracy: 0.8000\n",
            "Epoch 2399/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1824 - accuracy: 1.0000 - val_loss: 0.4819 - val_accuracy: 0.8000\n",
            "Epoch 2400/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2447 - accuracy: 0.9667 - val_loss: 0.4840 - val_accuracy: 0.8000\n",
            "Epoch 2401/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3569 - accuracy: 0.8000 - val_loss: 0.4864 - val_accuracy: 0.8000\n",
            "Epoch 2402/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2970 - accuracy: 0.8000 - val_loss: 0.4871 - val_accuracy: 0.8000\n",
            "Epoch 2403/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2902 - accuracy: 0.9000 - val_loss: 0.4865 - val_accuracy: 0.8000\n",
            "Epoch 2404/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2292 - accuracy: 0.9333 - val_loss: 0.4855 - val_accuracy: 0.8000\n",
            "Epoch 2405/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1711 - accuracy: 0.9667 - val_loss: 0.4861 - val_accuracy: 0.8000\n",
            "Epoch 2406/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1957 - accuracy: 0.9667 - val_loss: 0.4864 - val_accuracy: 0.8000\n",
            "Epoch 2407/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2059 - accuracy: 0.9333 - val_loss: 0.4867 - val_accuracy: 0.8000\n",
            "Epoch 2408/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.3015 - accuracy: 0.9333 - val_loss: 0.4878 - val_accuracy: 0.8000\n",
            "Epoch 2409/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2114 - accuracy: 0.9667 - val_loss: 0.4897 - val_accuracy: 0.8000\n",
            "Epoch 2410/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3137 - accuracy: 0.8333 - val_loss: 0.4904 - val_accuracy: 0.7857\n",
            "Epoch 2411/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2016 - accuracy: 0.9333 - val_loss: 0.4907 - val_accuracy: 0.7857\n",
            "Epoch 2412/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1734 - accuracy: 0.9667 - val_loss: 0.4918 - val_accuracy: 0.7714\n",
            "Epoch 2413/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1752 - accuracy: 0.9333 - val_loss: 0.4925 - val_accuracy: 0.7714\n",
            "Epoch 2414/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2695 - accuracy: 0.8333 - val_loss: 0.4918 - val_accuracy: 0.7714\n",
            "Epoch 2415/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2688 - accuracy: 0.8667 - val_loss: 0.4895 - val_accuracy: 0.7714\n",
            "Epoch 2416/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2251 - accuracy: 0.9667 - val_loss: 0.4872 - val_accuracy: 0.7857\n",
            "Epoch 2417/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2055 - accuracy: 0.9667 - val_loss: 0.4854 - val_accuracy: 0.7857\n",
            "Epoch 2418/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1842 - accuracy: 0.9333 - val_loss: 0.4839 - val_accuracy: 0.7857\n",
            "Epoch 2419/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1981 - accuracy: 0.9333 - val_loss: 0.4814 - val_accuracy: 0.7857\n",
            "Epoch 2420/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2670 - accuracy: 0.9000 - val_loss: 0.4794 - val_accuracy: 0.7857\n",
            "Epoch 2421/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2226 - accuracy: 0.9333 - val_loss: 0.4781 - val_accuracy: 0.7857\n",
            "Epoch 2422/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2595 - accuracy: 0.9333 - val_loss: 0.4766 - val_accuracy: 0.7857\n",
            "Epoch 2423/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2603 - accuracy: 0.9000 - val_loss: 0.4745 - val_accuracy: 0.7857\n",
            "Epoch 2424/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2365 - accuracy: 0.9333 - val_loss: 0.4725 - val_accuracy: 0.7857\n",
            "Epoch 2425/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1798 - accuracy: 0.9333 - val_loss: 0.4706 - val_accuracy: 0.7857\n",
            "Epoch 2426/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2265 - accuracy: 0.9333 - val_loss: 0.4685 - val_accuracy: 0.7857\n",
            "Epoch 2427/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2577 - accuracy: 0.9000 - val_loss: 0.4655 - val_accuracy: 0.7857\n",
            "Epoch 2428/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1882 - accuracy: 0.9667 - val_loss: 0.4623 - val_accuracy: 0.7571\n",
            "Epoch 2429/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2216 - accuracy: 0.8667 - val_loss: 0.4591 - val_accuracy: 0.7857\n",
            "Epoch 2430/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2526 - accuracy: 0.8667 - val_loss: 0.4568 - val_accuracy: 0.7857\n",
            "Epoch 2431/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2378 - accuracy: 0.9333 - val_loss: 0.4556 - val_accuracy: 0.8000\n",
            "Epoch 2432/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2528 - accuracy: 0.9000 - val_loss: 0.4544 - val_accuracy: 0.8000\n",
            "Epoch 2433/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2439 - accuracy: 0.9333 - val_loss: 0.4541 - val_accuracy: 0.8000\n",
            "Epoch 2434/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2370 - accuracy: 0.9333 - val_loss: 0.4541 - val_accuracy: 0.8000\n",
            "Epoch 2435/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1494 - accuracy: 0.9667 - val_loss: 0.4545 - val_accuracy: 0.7857\n",
            "Epoch 2436/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2359 - accuracy: 0.9000 - val_loss: 0.4558 - val_accuracy: 0.7714\n",
            "Epoch 2437/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2280 - accuracy: 0.9000 - val_loss: 0.4572 - val_accuracy: 0.7857\n",
            "Epoch 2438/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.3170 - accuracy: 0.8667 - val_loss: 0.4599 - val_accuracy: 0.8000\n",
            "Epoch 2439/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.3007 - accuracy: 0.8667 - val_loss: 0.4628 - val_accuracy: 0.8000\n",
            "Epoch 2440/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2201 - accuracy: 0.9333 - val_loss: 0.4652 - val_accuracy: 0.7857\n",
            "Epoch 2441/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1995 - accuracy: 0.9333 - val_loss: 0.4682 - val_accuracy: 0.7857\n",
            "Epoch 2442/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2370 - accuracy: 0.9000 - val_loss: 0.4720 - val_accuracy: 0.7857\n",
            "Epoch 2443/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2216 - accuracy: 0.9667 - val_loss: 0.4755 - val_accuracy: 0.8000\n",
            "Epoch 2444/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2135 - accuracy: 0.9000 - val_loss: 0.4778 - val_accuracy: 0.8000\n",
            "Epoch 2445/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2301 - accuracy: 0.9000 - val_loss: 0.4792 - val_accuracy: 0.8000\n",
            "Epoch 2446/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2570 - accuracy: 0.9000 - val_loss: 0.4796 - val_accuracy: 0.8000\n",
            "Epoch 2447/4000\n",
            "1/1 [==============================] - 0s 38ms/step - loss: 0.1932 - accuracy: 0.9333 - val_loss: 0.4804 - val_accuracy: 0.8000\n",
            "Epoch 2448/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2082 - accuracy: 0.9000 - val_loss: 0.4807 - val_accuracy: 0.8000\n",
            "Epoch 2449/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1799 - accuracy: 0.9333 - val_loss: 0.4823 - val_accuracy: 0.7857\n",
            "Epoch 2450/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1710 - accuracy: 0.9667 - val_loss: 0.4838 - val_accuracy: 0.7714\n",
            "Epoch 2451/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2482 - accuracy: 0.9000 - val_loss: 0.4836 - val_accuracy: 0.7714\n",
            "Epoch 2452/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2533 - accuracy: 0.9000 - val_loss: 0.4837 - val_accuracy: 0.7857\n",
            "Epoch 2453/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1882 - accuracy: 0.9333 - val_loss: 0.4844 - val_accuracy: 0.7714\n",
            "Epoch 2454/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1845 - accuracy: 1.0000 - val_loss: 0.4853 - val_accuracy: 0.7714\n",
            "Epoch 2455/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1499 - accuracy: 1.0000 - val_loss: 0.4866 - val_accuracy: 0.7714\n",
            "Epoch 2456/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1791 - accuracy: 0.9333 - val_loss: 0.4889 - val_accuracy: 0.7714\n",
            "Epoch 2457/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2542 - accuracy: 0.9000 - val_loss: 0.4908 - val_accuracy: 0.7714\n",
            "Epoch 2458/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2547 - accuracy: 0.9000 - val_loss: 0.4916 - val_accuracy: 0.7714\n",
            "Epoch 2459/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1525 - accuracy: 0.9667 - val_loss: 0.4924 - val_accuracy: 0.7714\n",
            "Epoch 2460/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1749 - accuracy: 0.9333 - val_loss: 0.4920 - val_accuracy: 0.7714\n",
            "Epoch 2461/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1974 - accuracy: 0.9667 - val_loss: 0.4907 - val_accuracy: 0.7714\n",
            "Epoch 2462/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2676 - accuracy: 0.9000 - val_loss: 0.4897 - val_accuracy: 0.7714\n",
            "Epoch 2463/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2686 - accuracy: 0.9333 - val_loss: 0.4887 - val_accuracy: 0.7714\n",
            "Epoch 2464/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2321 - accuracy: 0.8667 - val_loss: 0.4857 - val_accuracy: 0.8000\n",
            "Epoch 2465/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1881 - accuracy: 0.9333 - val_loss: 0.4833 - val_accuracy: 0.8000\n",
            "Epoch 2466/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2439 - accuracy: 0.9000 - val_loss: 0.4806 - val_accuracy: 0.8000\n",
            "Epoch 2467/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1542 - accuracy: 0.9667 - val_loss: 0.4781 - val_accuracy: 0.8000\n",
            "Epoch 2468/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2521 - accuracy: 0.8667 - val_loss: 0.4759 - val_accuracy: 0.8000\n",
            "Epoch 2469/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2624 - accuracy: 1.0000 - val_loss: 0.4741 - val_accuracy: 0.8000\n",
            "Epoch 2470/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2155 - accuracy: 0.9667 - val_loss: 0.4743 - val_accuracy: 0.8000\n",
            "Epoch 2471/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2505 - accuracy: 0.8667 - val_loss: 0.4769 - val_accuracy: 0.8000\n",
            "Epoch 2472/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2081 - accuracy: 0.9333 - val_loss: 0.4796 - val_accuracy: 0.8000\n",
            "Epoch 2473/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1803 - accuracy: 0.9333 - val_loss: 0.4821 - val_accuracy: 0.7857\n",
            "Epoch 2474/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2485 - accuracy: 0.9333 - val_loss: 0.4857 - val_accuracy: 0.7857\n",
            "Epoch 2475/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2288 - accuracy: 0.9000 - val_loss: 0.4902 - val_accuracy: 0.7714\n",
            "Epoch 2476/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2767 - accuracy: 0.9000 - val_loss: 0.4935 - val_accuracy: 0.7714\n",
            "Epoch 2477/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2950 - accuracy: 0.8667 - val_loss: 0.4962 - val_accuracy: 0.7714\n",
            "Epoch 2478/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2362 - accuracy: 0.8667 - val_loss: 0.4994 - val_accuracy: 0.7571\n",
            "Epoch 2479/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1929 - accuracy: 0.9667 - val_loss: 0.5023 - val_accuracy: 0.7571\n",
            "Epoch 2480/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2152 - accuracy: 0.9333 - val_loss: 0.5049 - val_accuracy: 0.7571\n",
            "Epoch 2481/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2731 - accuracy: 0.8667 - val_loss: 0.5050 - val_accuracy: 0.7571\n",
            "Epoch 2482/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2606 - accuracy: 0.9333 - val_loss: 0.5055 - val_accuracy: 0.7571\n",
            "Epoch 2483/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1541 - accuracy: 0.9000 - val_loss: 0.5064 - val_accuracy: 0.7571\n",
            "Epoch 2484/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2115 - accuracy: 0.9333 - val_loss: 0.5071 - val_accuracy: 0.7571\n",
            "Epoch 2485/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1979 - accuracy: 0.9000 - val_loss: 0.5088 - val_accuracy: 0.7571\n",
            "Epoch 2486/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2346 - accuracy: 0.9000 - val_loss: 0.5088 - val_accuracy: 0.7571\n",
            "Epoch 2487/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1928 - accuracy: 0.9333 - val_loss: 0.5088 - val_accuracy: 0.7571\n",
            "Epoch 2488/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2348 - accuracy: 0.9000 - val_loss: 0.5099 - val_accuracy: 0.7571\n",
            "Epoch 2489/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2082 - accuracy: 0.9000 - val_loss: 0.5098 - val_accuracy: 0.7571\n",
            "Epoch 2490/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2608 - accuracy: 0.9000 - val_loss: 0.5094 - val_accuracy: 0.7571\n",
            "Epoch 2491/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1906 - accuracy: 1.0000 - val_loss: 0.5092 - val_accuracy: 0.7571\n",
            "Epoch 2492/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.3119 - accuracy: 0.8333 - val_loss: 0.5087 - val_accuracy: 0.7571\n",
            "Epoch 2493/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2990 - accuracy: 0.8000 - val_loss: 0.5083 - val_accuracy: 0.7571\n",
            "Epoch 2494/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2241 - accuracy: 0.9333 - val_loss: 0.5094 - val_accuracy: 0.7571\n",
            "Epoch 2495/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2341 - accuracy: 0.9333 - val_loss: 0.5107 - val_accuracy: 0.7571\n",
            "Epoch 2496/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2123 - accuracy: 0.9000 - val_loss: 0.5120 - val_accuracy: 0.7571\n",
            "Epoch 2497/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2160 - accuracy: 0.9000 - val_loss: 0.5122 - val_accuracy: 0.7571\n",
            "Epoch 2498/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1608 - accuracy: 0.9667 - val_loss: 0.5118 - val_accuracy: 0.7571\n",
            "Epoch 2499/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2045 - accuracy: 0.9333 - val_loss: 0.5101 - val_accuracy: 0.7571\n",
            "Epoch 2500/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2152 - accuracy: 0.9000 - val_loss: 0.5076 - val_accuracy: 0.7571\n",
            "Epoch 2501/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2042 - accuracy: 0.9000 - val_loss: 0.5056 - val_accuracy: 0.7571\n",
            "Epoch 2502/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1947 - accuracy: 0.9333 - val_loss: 0.5032 - val_accuracy: 0.7714\n",
            "Epoch 2503/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1821 - accuracy: 0.9667 - val_loss: 0.5006 - val_accuracy: 0.7714\n",
            "Epoch 2504/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2010 - accuracy: 0.9000 - val_loss: 0.4985 - val_accuracy: 0.7857\n",
            "Epoch 2505/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3442 - accuracy: 0.9000 - val_loss: 0.4957 - val_accuracy: 0.7857\n",
            "Epoch 2506/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1980 - accuracy: 0.9333 - val_loss: 0.4926 - val_accuracy: 0.8000\n",
            "Epoch 2507/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2418 - accuracy: 0.9000 - val_loss: 0.4890 - val_accuracy: 0.7857\n",
            "Epoch 2508/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2663 - accuracy: 0.9000 - val_loss: 0.4864 - val_accuracy: 0.7857\n",
            "Epoch 2509/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2154 - accuracy: 0.9667 - val_loss: 0.4859 - val_accuracy: 0.7857\n",
            "Epoch 2510/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2198 - accuracy: 0.8667 - val_loss: 0.4854 - val_accuracy: 0.7857\n",
            "Epoch 2511/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1874 - accuracy: 0.9333 - val_loss: 0.4851 - val_accuracy: 0.7857\n",
            "Epoch 2512/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2352 - accuracy: 0.8667 - val_loss: 0.4848 - val_accuracy: 0.7857\n",
            "Epoch 2513/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2590 - accuracy: 0.9000 - val_loss: 0.4852 - val_accuracy: 0.7857\n",
            "Epoch 2514/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.1987 - accuracy: 0.9667 - val_loss: 0.4858 - val_accuracy: 0.7857\n",
            "Epoch 2515/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2521 - accuracy: 0.8667 - val_loss: 0.4878 - val_accuracy: 0.7857\n",
            "Epoch 2516/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1774 - accuracy: 0.9000 - val_loss: 0.4896 - val_accuracy: 0.7857\n",
            "Epoch 2517/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1718 - accuracy: 0.9667 - val_loss: 0.4913 - val_accuracy: 0.7857\n",
            "Epoch 2518/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2817 - accuracy: 0.9000 - val_loss: 0.4945 - val_accuracy: 0.7857\n",
            "Epoch 2519/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2603 - accuracy: 0.9333 - val_loss: 0.4985 - val_accuracy: 0.7714\n",
            "Epoch 2520/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2770 - accuracy: 0.8667 - val_loss: 0.5016 - val_accuracy: 0.7571\n",
            "Epoch 2521/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2669 - accuracy: 0.9333 - val_loss: 0.5043 - val_accuracy: 0.7571\n",
            "Epoch 2522/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2681 - accuracy: 0.8667 - val_loss: 0.5048 - val_accuracy: 0.7571\n",
            "Epoch 2523/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2457 - accuracy: 0.9000 - val_loss: 0.5063 - val_accuracy: 0.7571\n",
            "Epoch 2524/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1983 - accuracy: 0.9333 - val_loss: 0.5064 - val_accuracy: 0.7571\n",
            "Epoch 2525/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1664 - accuracy: 0.9667 - val_loss: 0.5065 - val_accuracy: 0.7571\n",
            "Epoch 2526/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1911 - accuracy: 0.9667 - val_loss: 0.5068 - val_accuracy: 0.7571\n",
            "Epoch 2527/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1832 - accuracy: 0.9333 - val_loss: 0.5070 - val_accuracy: 0.7571\n",
            "Epoch 2528/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2143 - accuracy: 0.9333 - val_loss: 0.5057 - val_accuracy: 0.7571\n",
            "Epoch 2529/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2261 - accuracy: 0.9333 - val_loss: 0.5033 - val_accuracy: 0.7571\n",
            "Epoch 2530/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2088 - accuracy: 0.9333 - val_loss: 0.5028 - val_accuracy: 0.7571\n",
            "Epoch 2531/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2072 - accuracy: 0.9333 - val_loss: 0.5005 - val_accuracy: 0.7571\n",
            "Epoch 2532/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2101 - accuracy: 0.9333 - val_loss: 0.4991 - val_accuracy: 0.7571\n",
            "Epoch 2533/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2571 - accuracy: 0.8667 - val_loss: 0.4974 - val_accuracy: 0.7571\n",
            "Epoch 2534/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2336 - accuracy: 0.8667 - val_loss: 0.4950 - val_accuracy: 0.7857\n",
            "Epoch 2535/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2132 - accuracy: 0.9333 - val_loss: 0.4931 - val_accuracy: 0.7857\n",
            "Epoch 2536/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2555 - accuracy: 0.8667 - val_loss: 0.4916 - val_accuracy: 0.7714\n",
            "Epoch 2537/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2517 - accuracy: 0.9000 - val_loss: 0.4896 - val_accuracy: 0.7857\n",
            "Epoch 2538/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1827 - accuracy: 0.9333 - val_loss: 0.4868 - val_accuracy: 0.7857\n",
            "Epoch 2539/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2254 - accuracy: 0.9333 - val_loss: 0.4846 - val_accuracy: 0.7857\n",
            "Epoch 2540/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2004 - accuracy: 0.9333 - val_loss: 0.4834 - val_accuracy: 0.7857\n",
            "Epoch 2541/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2546 - accuracy: 0.9000 - val_loss: 0.4820 - val_accuracy: 0.7857\n",
            "Epoch 2542/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2010 - accuracy: 0.9667 - val_loss: 0.4809 - val_accuracy: 0.8000\n",
            "Epoch 2543/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2269 - accuracy: 0.9333 - val_loss: 0.4808 - val_accuracy: 0.8000\n",
            "Epoch 2544/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2127 - accuracy: 0.9333 - val_loss: 0.4808 - val_accuracy: 0.8000\n",
            "Epoch 2545/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1891 - accuracy: 0.9333 - val_loss: 0.4808 - val_accuracy: 0.8000\n",
            "Epoch 2546/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2517 - accuracy: 0.8667 - val_loss: 0.4812 - val_accuracy: 0.8000\n",
            "Epoch 2547/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2274 - accuracy: 0.9000 - val_loss: 0.4822 - val_accuracy: 0.8000\n",
            "Epoch 2548/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1778 - accuracy: 0.9667 - val_loss: 0.4836 - val_accuracy: 0.8000\n",
            "Epoch 2549/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2998 - accuracy: 0.9000 - val_loss: 0.4853 - val_accuracy: 0.8000\n",
            "Epoch 2550/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1978 - accuracy: 0.9667 - val_loss: 0.4864 - val_accuracy: 0.7857\n",
            "Epoch 2551/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2344 - accuracy: 0.8667 - val_loss: 0.4876 - val_accuracy: 0.7857\n",
            "Epoch 2552/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2240 - accuracy: 0.8667 - val_loss: 0.4908 - val_accuracy: 0.7857\n",
            "Epoch 2553/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1859 - accuracy: 0.9333 - val_loss: 0.4939 - val_accuracy: 0.7857\n",
            "Epoch 2554/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2551 - accuracy: 0.9000 - val_loss: 0.4959 - val_accuracy: 0.7857\n",
            "Epoch 2555/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1996 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7571\n",
            "Epoch 2556/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1799 - accuracy: 0.9667 - val_loss: 0.5001 - val_accuracy: 0.7571\n",
            "Epoch 2557/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1989 - accuracy: 0.9000 - val_loss: 0.5011 - val_accuracy: 0.7571\n",
            "Epoch 2558/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2449 - accuracy: 0.9333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 2559/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2416 - accuracy: 0.9000 - val_loss: 0.5012 - val_accuracy: 0.7571\n",
            "Epoch 2560/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2024 - accuracy: 0.9333 - val_loss: 0.4998 - val_accuracy: 0.7571\n",
            "Epoch 2561/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1861 - accuracy: 0.9333 - val_loss: 0.4979 - val_accuracy: 0.7571\n",
            "Epoch 2562/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2010 - accuracy: 0.9667 - val_loss: 0.4974 - val_accuracy: 0.7571\n",
            "Epoch 2563/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2202 - accuracy: 0.9333 - val_loss: 0.4968 - val_accuracy: 0.7571\n",
            "Epoch 2564/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1787 - accuracy: 0.9333 - val_loss: 0.4969 - val_accuracy: 0.7571\n",
            "Epoch 2565/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1454 - accuracy: 0.9667 - val_loss: 0.4964 - val_accuracy: 0.7571\n",
            "Epoch 2566/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2498 - accuracy: 0.9000 - val_loss: 0.4951 - val_accuracy: 0.7571\n",
            "Epoch 2567/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1679 - accuracy: 0.9667 - val_loss: 0.4949 - val_accuracy: 0.7571\n",
            "Epoch 2568/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1801 - accuracy: 0.9333 - val_loss: 0.4939 - val_accuracy: 0.7571\n",
            "Epoch 2569/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1827 - accuracy: 0.9000 - val_loss: 0.4930 - val_accuracy: 0.7571\n",
            "Epoch 2570/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1566 - accuracy: 0.9667 - val_loss: 0.4940 - val_accuracy: 0.7571\n",
            "Epoch 2571/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2597 - accuracy: 0.9000 - val_loss: 0.4955 - val_accuracy: 0.7571\n",
            "Epoch 2572/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.3157 - accuracy: 0.9000 - val_loss: 0.4968 - val_accuracy: 0.7571\n",
            "Epoch 2573/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2286 - accuracy: 0.9333 - val_loss: 0.4966 - val_accuracy: 0.7571\n",
            "Epoch 2574/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2688 - accuracy: 0.8667 - val_loss: 0.4954 - val_accuracy: 0.7571\n",
            "Epoch 2575/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1840 - accuracy: 0.9333 - val_loss: 0.4942 - val_accuracy: 0.7571\n",
            "Epoch 2576/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2373 - accuracy: 0.8333 - val_loss: 0.4929 - val_accuracy: 0.7714\n",
            "Epoch 2577/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1624 - accuracy: 1.0000 - val_loss: 0.4919 - val_accuracy: 0.7714\n",
            "Epoch 2578/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2163 - accuracy: 0.9333 - val_loss: 0.4906 - val_accuracy: 0.7714\n",
            "Epoch 2579/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1766 - accuracy: 0.9667 - val_loss: 0.4896 - val_accuracy: 0.7857\n",
            "Epoch 2580/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2830 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.7857\n",
            "Epoch 2581/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2533 - accuracy: 0.9000 - val_loss: 0.4888 - val_accuracy: 0.7857\n",
            "Epoch 2582/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2393 - accuracy: 0.9000 - val_loss: 0.4890 - val_accuracy: 0.7857\n",
            "Epoch 2583/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1932 - accuracy: 0.9333 - val_loss: 0.4896 - val_accuracy: 0.7857\n",
            "Epoch 2584/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3123 - accuracy: 0.8333 - val_loss: 0.4899 - val_accuracy: 0.7857\n",
            "Epoch 2585/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2138 - accuracy: 0.9000 - val_loss: 0.4906 - val_accuracy: 0.7857\n",
            "Epoch 2586/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1745 - accuracy: 0.9333 - val_loss: 0.4918 - val_accuracy: 0.7857\n",
            "Epoch 2587/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2068 - accuracy: 0.9000 - val_loss: 0.4927 - val_accuracy: 0.7714\n",
            "Epoch 2588/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2398 - accuracy: 0.9667 - val_loss: 0.4935 - val_accuracy: 0.7714\n",
            "Epoch 2589/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1563 - accuracy: 0.9667 - val_loss: 0.4958 - val_accuracy: 0.7714\n",
            "Epoch 2590/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1862 - accuracy: 0.9333 - val_loss: 0.4986 - val_accuracy: 0.7714\n",
            "Epoch 2591/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2952 - accuracy: 0.9000 - val_loss: 0.5010 - val_accuracy: 0.7714\n",
            "Epoch 2592/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.2006 - accuracy: 0.9000 - val_loss: 0.5034 - val_accuracy: 0.7714\n",
            "Epoch 2593/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2519 - accuracy: 0.8667 - val_loss: 0.5038 - val_accuracy: 0.7714\n",
            "Epoch 2594/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2026 - accuracy: 0.9000 - val_loss: 0.5042 - val_accuracy: 0.7714\n",
            "Epoch 2595/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2475 - accuracy: 0.9000 - val_loss: 0.5026 - val_accuracy: 0.7714\n",
            "Epoch 2596/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2287 - accuracy: 0.9667 - val_loss: 0.5005 - val_accuracy: 0.7571\n",
            "Epoch 2597/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2107 - accuracy: 0.9000 - val_loss: 0.4981 - val_accuracy: 0.7714\n",
            "Epoch 2598/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2157 - accuracy: 0.9000 - val_loss: 0.4963 - val_accuracy: 0.7857\n",
            "Epoch 2599/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2427 - accuracy: 0.9000 - val_loss: 0.4939 - val_accuracy: 0.7857\n",
            "Epoch 2600/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1432 - accuracy: 0.9667 - val_loss: 0.4922 - val_accuracy: 0.7857\n",
            "Epoch 2601/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2029 - accuracy: 0.9667 - val_loss: 0.4910 - val_accuracy: 0.7857\n",
            "Epoch 2602/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2233 - accuracy: 0.9667 - val_loss: 0.4900 - val_accuracy: 0.8000\n",
            "Epoch 2603/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2039 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.8000\n",
            "Epoch 2604/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2714 - accuracy: 0.8333 - val_loss: 0.4870 - val_accuracy: 0.8000\n",
            "Epoch 2605/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2454 - accuracy: 0.9000 - val_loss: 0.4851 - val_accuracy: 0.8000\n",
            "Epoch 2606/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1748 - accuracy: 0.9667 - val_loss: 0.4836 - val_accuracy: 0.8000\n",
            "Epoch 2607/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2769 - accuracy: 0.9000 - val_loss: 0.4815 - val_accuracy: 0.8000\n",
            "Epoch 2608/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1228 - accuracy: 1.0000 - val_loss: 0.4798 - val_accuracy: 0.8000\n",
            "Epoch 2609/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2428 - accuracy: 0.8667 - val_loss: 0.4792 - val_accuracy: 0.8000\n",
            "Epoch 2610/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.3735 - accuracy: 0.8333 - val_loss: 0.4781 - val_accuracy: 0.8000\n",
            "Epoch 2611/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2196 - accuracy: 0.9000 - val_loss: 0.4781 - val_accuracy: 0.7714\n",
            "Epoch 2612/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1922 - accuracy: 0.9667 - val_loss: 0.4782 - val_accuracy: 0.7714\n",
            "Epoch 2613/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2714 - accuracy: 0.8667 - val_loss: 0.4784 - val_accuracy: 0.7714\n",
            "Epoch 2614/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1704 - accuracy: 0.9667 - val_loss: 0.4786 - val_accuracy: 0.7714\n",
            "Epoch 2615/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2265 - accuracy: 0.8667 - val_loss: 0.4796 - val_accuracy: 0.7714\n",
            "Epoch 2616/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2088 - accuracy: 0.9333 - val_loss: 0.4825 - val_accuracy: 0.7857\n",
            "Epoch 2617/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.4491 - accuracy: 0.7333 - val_loss: 0.4854 - val_accuracy: 0.7857\n",
            "Epoch 2618/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2205 - accuracy: 0.8667 - val_loss: 0.4887 - val_accuracy: 0.7857\n",
            "Epoch 2619/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1957 - accuracy: 0.9667 - val_loss: 0.4908 - val_accuracy: 0.7857\n",
            "Epoch 2620/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2205 - accuracy: 0.9333 - val_loss: 0.4911 - val_accuracy: 0.7857\n",
            "Epoch 2621/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2624 - accuracy: 0.9000 - val_loss: 0.4927 - val_accuracy: 0.7857\n",
            "Epoch 2622/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2488 - accuracy: 0.9000 - val_loss: 0.4931 - val_accuracy: 0.7857\n",
            "Epoch 2623/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1911 - accuracy: 0.9667 - val_loss: 0.4937 - val_accuracy: 0.7857\n",
            "Epoch 2624/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2489 - accuracy: 0.9000 - val_loss: 0.4937 - val_accuracy: 0.7857\n",
            "Epoch 2625/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1841 - accuracy: 0.9333 - val_loss: 0.4948 - val_accuracy: 0.7857\n",
            "Epoch 2626/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2174 - accuracy: 0.9000 - val_loss: 0.4960 - val_accuracy: 0.7857\n",
            "Epoch 2627/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2641 - accuracy: 0.9000 - val_loss: 0.4989 - val_accuracy: 0.7857\n",
            "Epoch 2628/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2046 - accuracy: 0.9667 - val_loss: 0.5018 - val_accuracy: 0.7714\n",
            "Epoch 2629/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1979 - accuracy: 0.9667 - val_loss: 0.5051 - val_accuracy: 0.7571\n",
            "Epoch 2630/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1574 - accuracy: 0.9667 - val_loss: 0.5080 - val_accuracy: 0.7714\n",
            "Epoch 2631/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.3115 - accuracy: 0.9000 - val_loss: 0.5107 - val_accuracy: 0.7714\n",
            "Epoch 2632/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1984 - accuracy: 0.9333 - val_loss: 0.5135 - val_accuracy: 0.7714\n",
            "Epoch 2633/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.3659 - accuracy: 0.8667 - val_loss: 0.5162 - val_accuracy: 0.7714\n",
            "Epoch 2634/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2385 - accuracy: 0.9333 - val_loss: 0.5188 - val_accuracy: 0.7714\n",
            "Epoch 2635/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2133 - accuracy: 0.8667 - val_loss: 0.5215 - val_accuracy: 0.7714\n",
            "Epoch 2636/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2540 - accuracy: 0.8667 - val_loss: 0.5223 - val_accuracy: 0.7714\n",
            "Epoch 2637/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2319 - accuracy: 0.9333 - val_loss: 0.5216 - val_accuracy: 0.7714\n",
            "Epoch 2638/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2208 - accuracy: 0.8667 - val_loss: 0.5199 - val_accuracy: 0.7714\n",
            "Epoch 2639/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1828 - accuracy: 0.9333 - val_loss: 0.5186 - val_accuracy: 0.7714\n",
            "Epoch 2640/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1684 - accuracy: 0.9333 - val_loss: 0.5168 - val_accuracy: 0.7714\n",
            "Epoch 2641/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2339 - accuracy: 0.9333 - val_loss: 0.5141 - val_accuracy: 0.7714\n",
            "Epoch 2642/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2403 - accuracy: 0.8333 - val_loss: 0.5119 - val_accuracy: 0.7714\n",
            "Epoch 2643/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2349 - accuracy: 0.9333 - val_loss: 0.5093 - val_accuracy: 0.7857\n",
            "Epoch 2644/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2218 - accuracy: 0.9333 - val_loss: 0.5073 - val_accuracy: 0.7857\n",
            "Epoch 2645/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1979 - accuracy: 0.9333 - val_loss: 0.5063 - val_accuracy: 0.7857\n",
            "Epoch 2646/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2581 - accuracy: 0.9000 - val_loss: 0.5065 - val_accuracy: 0.7857\n",
            "Epoch 2647/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2145 - accuracy: 0.9667 - val_loss: 0.5056 - val_accuracy: 0.7857\n",
            "Epoch 2648/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2011 - accuracy: 0.9333 - val_loss: 0.5059 - val_accuracy: 0.7857\n",
            "Epoch 2649/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2712 - accuracy: 0.9000 - val_loss: 0.5040 - val_accuracy: 0.7857\n",
            "Epoch 2650/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1906 - accuracy: 0.9667 - val_loss: 0.5020 - val_accuracy: 0.7857\n",
            "Epoch 2651/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1763 - accuracy: 0.9667 - val_loss: 0.5005 - val_accuracy: 0.8000\n",
            "Epoch 2652/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1871 - accuracy: 0.9333 - val_loss: 0.4990 - val_accuracy: 0.8000\n",
            "Epoch 2653/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1775 - accuracy: 0.9333 - val_loss: 0.4985 - val_accuracy: 0.7857\n",
            "Epoch 2654/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2155 - accuracy: 0.9000 - val_loss: 0.4977 - val_accuracy: 0.7857\n",
            "Epoch 2655/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2351 - accuracy: 0.9000 - val_loss: 0.4981 - val_accuracy: 0.7857\n",
            "Epoch 2656/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1668 - accuracy: 0.9333 - val_loss: 0.4993 - val_accuracy: 0.7857\n",
            "Epoch 2657/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1870 - accuracy: 0.9667 - val_loss: 0.5018 - val_accuracy: 0.7857\n",
            "Epoch 2658/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1312 - accuracy: 0.9667 - val_loss: 0.5041 - val_accuracy: 0.7714\n",
            "Epoch 2659/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2307 - accuracy: 0.9333 - val_loss: 0.5061 - val_accuracy: 0.7714\n",
            "Epoch 2660/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1893 - accuracy: 0.9000 - val_loss: 0.5084 - val_accuracy: 0.7714\n",
            "Epoch 2661/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2702 - accuracy: 0.9000 - val_loss: 0.5081 - val_accuracy: 0.7714\n",
            "Epoch 2662/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2033 - accuracy: 0.9333 - val_loss: 0.5066 - val_accuracy: 0.7714\n",
            "Epoch 2663/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2128 - accuracy: 0.9333 - val_loss: 0.5057 - val_accuracy: 0.7714\n",
            "Epoch 2664/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1735 - accuracy: 0.9667 - val_loss: 0.5052 - val_accuracy: 0.7857\n",
            "Epoch 2665/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2057 - accuracy: 0.9333 - val_loss: 0.5046 - val_accuracy: 0.8000\n",
            "Epoch 2666/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2648 - accuracy: 0.9333 - val_loss: 0.5025 - val_accuracy: 0.8000\n",
            "Epoch 2667/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1762 - accuracy: 0.9667 - val_loss: 0.5009 - val_accuracy: 0.7857\n",
            "Epoch 2668/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1507 - accuracy: 1.0000 - val_loss: 0.5005 - val_accuracy: 0.7857\n",
            "Epoch 2669/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2014 - accuracy: 0.9000 - val_loss: 0.5006 - val_accuracy: 0.7857\n",
            "Epoch 2670/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1722 - accuracy: 0.9333 - val_loss: 0.5009 - val_accuracy: 0.7857\n",
            "Epoch 2671/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1909 - accuracy: 0.9667 - val_loss: 0.5008 - val_accuracy: 0.7857\n",
            "Epoch 2672/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1885 - accuracy: 0.9333 - val_loss: 0.5008 - val_accuracy: 0.7857\n",
            "Epoch 2673/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2105 - accuracy: 0.9333 - val_loss: 0.4997 - val_accuracy: 0.7857\n",
            "Epoch 2674/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2339 - accuracy: 0.9000 - val_loss: 0.4982 - val_accuracy: 0.7857\n",
            "Epoch 2675/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1935 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7857\n",
            "Epoch 2676/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2275 - accuracy: 0.9000 - val_loss: 0.4984 - val_accuracy: 0.8000\n",
            "Epoch 2677/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2816 - accuracy: 0.9000 - val_loss: 0.4985 - val_accuracy: 0.8000\n",
            "Epoch 2678/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1733 - accuracy: 0.9667 - val_loss: 0.4994 - val_accuracy: 0.8000\n",
            "Epoch 2679/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2033 - accuracy: 0.9000 - val_loss: 0.5001 - val_accuracy: 0.7857\n",
            "Epoch 2680/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2340 - accuracy: 0.9333 - val_loss: 0.4994 - val_accuracy: 0.7857\n",
            "Epoch 2681/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1629 - accuracy: 0.9333 - val_loss: 0.4995 - val_accuracy: 0.7857\n",
            "Epoch 2682/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1826 - accuracy: 0.9667 - val_loss: 0.4995 - val_accuracy: 0.7857\n",
            "Epoch 2683/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1765 - accuracy: 0.9667 - val_loss: 0.4991 - val_accuracy: 0.7857\n",
            "Epoch 2684/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2000 - accuracy: 0.9667 - val_loss: 0.4983 - val_accuracy: 0.7857\n",
            "Epoch 2685/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2989 - accuracy: 0.9000 - val_loss: 0.4974 - val_accuracy: 0.7857\n",
            "Epoch 2686/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2153 - accuracy: 0.9000 - val_loss: 0.4961 - val_accuracy: 0.7857\n",
            "Epoch 2687/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2211 - accuracy: 0.9333 - val_loss: 0.4955 - val_accuracy: 0.7857\n",
            "Epoch 2688/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2233 - accuracy: 0.9000 - val_loss: 0.4943 - val_accuracy: 0.7857\n",
            "Epoch 2689/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2008 - accuracy: 0.9000 - val_loss: 0.4920 - val_accuracy: 0.7857\n",
            "Epoch 2690/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1872 - accuracy: 0.8667 - val_loss: 0.4895 - val_accuracy: 0.7857\n",
            "Epoch 2691/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2120 - accuracy: 0.9333 - val_loss: 0.4878 - val_accuracy: 0.7857\n",
            "Epoch 2692/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.3058 - accuracy: 0.8667 - val_loss: 0.4862 - val_accuracy: 0.7857\n",
            "Epoch 2693/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1628 - accuracy: 1.0000 - val_loss: 0.4849 - val_accuracy: 0.7857\n",
            "Epoch 2694/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1953 - accuracy: 0.9333 - val_loss: 0.4840 - val_accuracy: 0.7857\n",
            "Epoch 2695/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2326 - accuracy: 0.9333 - val_loss: 0.4841 - val_accuracy: 0.7857\n",
            "Epoch 2696/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2294 - accuracy: 0.9000 - val_loss: 0.4841 - val_accuracy: 0.7857\n",
            "Epoch 2697/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2390 - accuracy: 0.9333 - val_loss: 0.4845 - val_accuracy: 0.7857\n",
            "Epoch 2698/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2626 - accuracy: 0.9000 - val_loss: 0.4848 - val_accuracy: 0.7857\n",
            "Epoch 2699/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2501 - accuracy: 0.8667 - val_loss: 0.4869 - val_accuracy: 0.7857\n",
            "Epoch 2700/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2150 - accuracy: 0.9333 - val_loss: 0.4886 - val_accuracy: 0.7857\n",
            "Epoch 2701/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1984 - accuracy: 0.9000 - val_loss: 0.4913 - val_accuracy: 0.7857\n",
            "Epoch 2702/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2476 - accuracy: 0.9333 - val_loss: 0.4944 - val_accuracy: 0.7857\n",
            "Epoch 2703/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1920 - accuracy: 0.9667 - val_loss: 0.4966 - val_accuracy: 0.7857\n",
            "Epoch 2704/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1901 - accuracy: 0.9667 - val_loss: 0.4992 - val_accuracy: 0.7857\n",
            "Epoch 2705/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1825 - accuracy: 0.9333 - val_loss: 0.5002 - val_accuracy: 0.7857\n",
            "Epoch 2706/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2817 - accuracy: 0.8667 - val_loss: 0.5010 - val_accuracy: 0.7714\n",
            "Epoch 2707/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2287 - accuracy: 0.8667 - val_loss: 0.5023 - val_accuracy: 0.7714\n",
            "Epoch 2708/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2166 - accuracy: 0.9000 - val_loss: 0.5038 - val_accuracy: 0.7714\n",
            "Epoch 2709/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2292 - accuracy: 0.9000 - val_loss: 0.5065 - val_accuracy: 0.7714\n",
            "Epoch 2710/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2427 - accuracy: 0.9000 - val_loss: 0.5080 - val_accuracy: 0.7714\n",
            "Epoch 2711/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1864 - accuracy: 0.9333 - val_loss: 0.5091 - val_accuracy: 0.7714\n",
            "Epoch 2712/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2321 - accuracy: 0.9000 - val_loss: 0.5094 - val_accuracy: 0.7714\n",
            "Epoch 2713/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2052 - accuracy: 0.9667 - val_loss: 0.5080 - val_accuracy: 0.7714\n",
            "Epoch 2714/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1856 - accuracy: 0.9667 - val_loss: 0.5068 - val_accuracy: 0.7714\n",
            "Epoch 2715/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2388 - accuracy: 0.9000 - val_loss: 0.5047 - val_accuracy: 0.7714\n",
            "Epoch 2716/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2715 - accuracy: 0.9333 - val_loss: 0.5021 - val_accuracy: 0.7857\n",
            "Epoch 2717/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1505 - accuracy: 0.9333 - val_loss: 0.5006 - val_accuracy: 0.8000\n",
            "Epoch 2718/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1986 - accuracy: 0.9667 - val_loss: 0.4992 - val_accuracy: 0.8000\n",
            "Epoch 2719/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1960 - accuracy: 0.9333 - val_loss: 0.4989 - val_accuracy: 0.8000\n",
            "Epoch 2720/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1782 - accuracy: 0.9667 - val_loss: 0.4983 - val_accuracy: 0.8000\n",
            "Epoch 2721/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1602 - accuracy: 0.9667 - val_loss: 0.4992 - val_accuracy: 0.8000\n",
            "Epoch 2722/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2911 - accuracy: 0.8667 - val_loss: 0.4997 - val_accuracy: 0.8000\n",
            "Epoch 2723/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1674 - accuracy: 1.0000 - val_loss: 0.5017 - val_accuracy: 0.8000\n",
            "Epoch 2724/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2361 - accuracy: 0.8667 - val_loss: 0.5041 - val_accuracy: 0.8000\n",
            "Epoch 2725/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2255 - accuracy: 0.9000 - val_loss: 0.5066 - val_accuracy: 0.8000\n",
            "Epoch 2726/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2214 - accuracy: 0.9333 - val_loss: 0.5094 - val_accuracy: 0.7857\n",
            "Epoch 2727/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1836 - accuracy: 0.9333 - val_loss: 0.5125 - val_accuracy: 0.7714\n",
            "Epoch 2728/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2455 - accuracy: 0.9000 - val_loss: 0.5159 - val_accuracy: 0.7571\n",
            "Epoch 2729/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1958 - accuracy: 0.9667 - val_loss: 0.5198 - val_accuracy: 0.7571\n",
            "Epoch 2730/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1861 - accuracy: 0.9667 - val_loss: 0.5237 - val_accuracy: 0.7571\n",
            "Epoch 2731/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2134 - accuracy: 0.9333 - val_loss: 0.5275 - val_accuracy: 0.7571\n",
            "Epoch 2732/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2479 - accuracy: 0.9000 - val_loss: 0.5300 - val_accuracy: 0.7571\n",
            "Epoch 2733/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2157 - accuracy: 0.9000 - val_loss: 0.5309 - val_accuracy: 0.7571\n",
            "Epoch 2734/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1639 - accuracy: 0.9667 - val_loss: 0.5315 - val_accuracy: 0.7571\n",
            "Epoch 2735/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2416 - accuracy: 0.9333 - val_loss: 0.5324 - val_accuracy: 0.7571\n",
            "Epoch 2736/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1703 - accuracy: 0.9667 - val_loss: 0.5333 - val_accuracy: 0.7571\n",
            "Epoch 2737/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2290 - accuracy: 0.9333 - val_loss: 0.5340 - val_accuracy: 0.7571\n",
            "Epoch 2738/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2497 - accuracy: 0.9333 - val_loss: 0.5344 - val_accuracy: 0.7571\n",
            "Epoch 2739/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2008 - accuracy: 0.9667 - val_loss: 0.5343 - val_accuracy: 0.7571\n",
            "Epoch 2740/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2464 - accuracy: 0.9667 - val_loss: 0.5326 - val_accuracy: 0.7571\n",
            "Epoch 2741/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1760 - accuracy: 0.9667 - val_loss: 0.5309 - val_accuracy: 0.7714\n",
            "Epoch 2742/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2362 - accuracy: 0.8667 - val_loss: 0.5287 - val_accuracy: 0.7714\n",
            "Epoch 2743/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1532 - accuracy: 0.9667 - val_loss: 0.5266 - val_accuracy: 0.7714\n",
            "Epoch 2744/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2067 - accuracy: 0.8667 - val_loss: 0.5249 - val_accuracy: 0.7714\n",
            "Epoch 2745/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1583 - accuracy: 0.9667 - val_loss: 0.5229 - val_accuracy: 0.7714\n",
            "Epoch 2746/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2266 - accuracy: 0.9333 - val_loss: 0.5212 - val_accuracy: 0.7714\n",
            "Epoch 2747/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2339 - accuracy: 0.9000 - val_loss: 0.5185 - val_accuracy: 0.7714\n",
            "Epoch 2748/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1992 - accuracy: 0.9667 - val_loss: 0.5152 - val_accuracy: 0.7714\n",
            "Epoch 2749/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2107 - accuracy: 0.9333 - val_loss: 0.5130 - val_accuracy: 0.7714\n",
            "Epoch 2750/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1681 - accuracy: 0.9333 - val_loss: 0.5109 - val_accuracy: 0.7714\n",
            "Epoch 2751/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2261 - accuracy: 0.8667 - val_loss: 0.5077 - val_accuracy: 0.8000\n",
            "Epoch 2752/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2537 - accuracy: 0.9333 - val_loss: 0.5044 - val_accuracy: 0.8000\n",
            "Epoch 2753/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2570 - accuracy: 0.9000 - val_loss: 0.5020 - val_accuracy: 0.8000\n",
            "Epoch 2754/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1180 - accuracy: 1.0000 - val_loss: 0.5006 - val_accuracy: 0.8000\n",
            "Epoch 2755/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2073 - accuracy: 0.9333 - val_loss: 0.4987 - val_accuracy: 0.8000\n",
            "Epoch 2756/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2625 - accuracy: 0.9000 - val_loss: 0.4975 - val_accuracy: 0.8000\n",
            "Epoch 2757/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2223 - accuracy: 0.9000 - val_loss: 0.4968 - val_accuracy: 0.8000\n",
            "Epoch 2758/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2057 - accuracy: 0.9667 - val_loss: 0.4980 - val_accuracy: 0.8000\n",
            "Epoch 2759/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1815 - accuracy: 0.9333 - val_loss: 0.4997 - val_accuracy: 0.8000\n",
            "Epoch 2760/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2209 - accuracy: 0.8667 - val_loss: 0.5029 - val_accuracy: 0.8000\n",
            "Epoch 2761/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2223 - accuracy: 0.9667 - val_loss: 0.5054 - val_accuracy: 0.8000\n",
            "Epoch 2762/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2253 - accuracy: 0.9333 - val_loss: 0.5089 - val_accuracy: 0.7714\n",
            "Epoch 2763/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2423 - accuracy: 0.9000 - val_loss: 0.5125 - val_accuracy: 0.7714\n",
            "Epoch 2764/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2524 - accuracy: 0.9000 - val_loss: 0.5146 - val_accuracy: 0.7714\n",
            "Epoch 2765/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1994 - accuracy: 0.9333 - val_loss: 0.5162 - val_accuracy: 0.7714\n",
            "Epoch 2766/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2237 - accuracy: 0.9000 - val_loss: 0.5176 - val_accuracy: 0.7714\n",
            "Epoch 2767/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2486 - accuracy: 0.9000 - val_loss: 0.5190 - val_accuracy: 0.7714\n",
            "Epoch 2768/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2374 - accuracy: 0.8667 - val_loss: 0.5215 - val_accuracy: 0.7714\n",
            "Epoch 2769/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2202 - accuracy: 0.9000 - val_loss: 0.5236 - val_accuracy: 0.7714\n",
            "Epoch 2770/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2345 - accuracy: 0.8667 - val_loss: 0.5236 - val_accuracy: 0.7714\n",
            "Epoch 2771/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2490 - accuracy: 0.9000 - val_loss: 0.5240 - val_accuracy: 0.7714\n",
            "Epoch 2772/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1871 - accuracy: 0.9000 - val_loss: 0.5229 - val_accuracy: 0.7714\n",
            "Epoch 2773/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1783 - accuracy: 0.9333 - val_loss: 0.5225 - val_accuracy: 0.7714\n",
            "Epoch 2774/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2083 - accuracy: 0.9333 - val_loss: 0.5206 - val_accuracy: 0.7714\n",
            "Epoch 2775/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2337 - accuracy: 0.9333 - val_loss: 0.5200 - val_accuracy: 0.7714\n",
            "Epoch 2776/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1564 - accuracy: 0.9333 - val_loss: 0.5205 - val_accuracy: 0.7714\n",
            "Epoch 2777/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1427 - accuracy: 0.9667 - val_loss: 0.5196 - val_accuracy: 0.7714\n",
            "Epoch 2778/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2624 - accuracy: 0.8667 - val_loss: 0.5177 - val_accuracy: 0.7571\n",
            "Epoch 2779/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2653 - accuracy: 0.8667 - val_loss: 0.5158 - val_accuracy: 0.7571\n",
            "Epoch 2780/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2318 - accuracy: 0.8333 - val_loss: 0.5143 - val_accuracy: 0.7714\n",
            "Epoch 2781/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2550 - accuracy: 0.9333 - val_loss: 0.5135 - val_accuracy: 0.7714\n",
            "Epoch 2782/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1886 - accuracy: 0.9000 - val_loss: 0.5137 - val_accuracy: 0.7714\n",
            "Epoch 2783/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1723 - accuracy: 0.9667 - val_loss: 0.5141 - val_accuracy: 0.7714\n",
            "Epoch 2784/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2188 - accuracy: 0.8333 - val_loss: 0.5130 - val_accuracy: 0.7714\n",
            "Epoch 2785/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1946 - accuracy: 0.8667 - val_loss: 0.5129 - val_accuracy: 0.7571\n",
            "Epoch 2786/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2563 - accuracy: 0.8667 - val_loss: 0.5126 - val_accuracy: 0.7571\n",
            "Epoch 2787/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1536 - accuracy: 0.9333 - val_loss: 0.5121 - val_accuracy: 0.7571\n",
            "Epoch 2788/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2765 - accuracy: 0.8333 - val_loss: 0.5116 - val_accuracy: 0.7571\n",
            "Epoch 2789/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1786 - accuracy: 0.9333 - val_loss: 0.5114 - val_accuracy: 0.7571\n",
            "Epoch 2790/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1436 - accuracy: 0.9667 - val_loss: 0.5112 - val_accuracy: 0.7571\n",
            "Epoch 2791/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2358 - accuracy: 0.8667 - val_loss: 0.5121 - val_accuracy: 0.7571\n",
            "Epoch 2792/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1900 - accuracy: 0.9000 - val_loss: 0.5136 - val_accuracy: 0.7571\n",
            "Epoch 2793/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1678 - accuracy: 0.9333 - val_loss: 0.5145 - val_accuracy: 0.7571\n",
            "Epoch 2794/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2685 - accuracy: 0.8333 - val_loss: 0.5155 - val_accuracy: 0.7571\n",
            "Epoch 2795/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2395 - accuracy: 0.9000 - val_loss: 0.5165 - val_accuracy: 0.7571\n",
            "Epoch 2796/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2110 - accuracy: 0.9000 - val_loss: 0.5187 - val_accuracy: 0.7571\n",
            "Epoch 2797/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1584 - accuracy: 0.9667 - val_loss: 0.5198 - val_accuracy: 0.7571\n",
            "Epoch 2798/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1542 - accuracy: 0.9667 - val_loss: 0.5209 - val_accuracy: 0.7571\n",
            "Epoch 2799/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.2166 - accuracy: 0.9333 - val_loss: 0.5216 - val_accuracy: 0.7571\n",
            "Epoch 2800/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1432 - accuracy: 0.9667 - val_loss: 0.5216 - val_accuracy: 0.7571\n",
            "Epoch 2801/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2066 - accuracy: 0.9333 - val_loss: 0.5206 - val_accuracy: 0.7571\n",
            "Epoch 2802/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2083 - accuracy: 0.9000 - val_loss: 0.5202 - val_accuracy: 0.7571\n",
            "Epoch 2803/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1857 - accuracy: 0.9333 - val_loss: 0.5219 - val_accuracy: 0.7571\n",
            "Epoch 2804/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3197 - accuracy: 0.8000 - val_loss: 0.5220 - val_accuracy: 0.7571\n",
            "Epoch 2805/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1776 - accuracy: 1.0000 - val_loss: 0.5219 - val_accuracy: 0.7571\n",
            "Epoch 2806/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1693 - accuracy: 0.9333 - val_loss: 0.5228 - val_accuracy: 0.7571\n",
            "Epoch 2807/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2575 - accuracy: 0.9000 - val_loss: 0.5233 - val_accuracy: 0.7714\n",
            "Epoch 2808/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2515 - accuracy: 0.9000 - val_loss: 0.5222 - val_accuracy: 0.7714\n",
            "Epoch 2809/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2374 - accuracy: 0.8667 - val_loss: 0.5221 - val_accuracy: 0.7714\n",
            "Epoch 2810/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2509 - accuracy: 0.9000 - val_loss: 0.5225 - val_accuracy: 0.7714\n",
            "Epoch 2811/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1822 - accuracy: 0.9667 - val_loss: 0.5221 - val_accuracy: 0.7714\n",
            "Epoch 2812/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1940 - accuracy: 1.0000 - val_loss: 0.5216 - val_accuracy: 0.7714\n",
            "Epoch 2813/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1774 - accuracy: 0.9667 - val_loss: 0.5214 - val_accuracy: 0.7714\n",
            "Epoch 2814/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2013 - accuracy: 0.9000 - val_loss: 0.5210 - val_accuracy: 0.7714\n",
            "Epoch 2815/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2234 - accuracy: 0.8667 - val_loss: 0.5191 - val_accuracy: 0.7714\n",
            "Epoch 2816/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2306 - accuracy: 0.9000 - val_loss: 0.5165 - val_accuracy: 0.7714\n",
            "Epoch 2817/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2012 - accuracy: 0.9000 - val_loss: 0.5137 - val_accuracy: 0.7857\n",
            "Epoch 2818/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2166 - accuracy: 0.9000 - val_loss: 0.5112 - val_accuracy: 0.7857\n",
            "Epoch 2819/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1987 - accuracy: 0.9333 - val_loss: 0.5091 - val_accuracy: 0.7857\n",
            "Epoch 2820/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1936 - accuracy: 0.9333 - val_loss: 0.5082 - val_accuracy: 0.7714\n",
            "Epoch 2821/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2426 - accuracy: 0.8667 - val_loss: 0.5069 - val_accuracy: 0.7857\n",
            "Epoch 2822/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1908 - accuracy: 0.9333 - val_loss: 0.5059 - val_accuracy: 0.7857\n",
            "Epoch 2823/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2161 - accuracy: 0.9333 - val_loss: 0.5047 - val_accuracy: 0.7857\n",
            "Epoch 2824/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2587 - accuracy: 0.9333 - val_loss: 0.5036 - val_accuracy: 0.7857\n",
            "Epoch 2825/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2999 - accuracy: 0.9333 - val_loss: 0.5032 - val_accuracy: 0.7857\n",
            "Epoch 2826/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1630 - accuracy: 0.9333 - val_loss: 0.5038 - val_accuracy: 0.8000\n",
            "Epoch 2827/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2550 - accuracy: 0.9000 - val_loss: 0.5022 - val_accuracy: 0.8000\n",
            "Epoch 2828/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1219 - accuracy: 0.9333 - val_loss: 0.5009 - val_accuracy: 0.8000\n",
            "Epoch 2829/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1254 - accuracy: 0.9667 - val_loss: 0.5002 - val_accuracy: 0.8000\n",
            "Epoch 2830/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1351 - accuracy: 0.9667 - val_loss: 0.4996 - val_accuracy: 0.8000\n",
            "Epoch 2831/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1633 - accuracy: 0.9333 - val_loss: 0.4986 - val_accuracy: 0.8000\n",
            "Epoch 2832/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1962 - accuracy: 0.9000 - val_loss: 0.4969 - val_accuracy: 0.8000\n",
            "Epoch 2833/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2400 - accuracy: 0.9000 - val_loss: 0.4944 - val_accuracy: 0.8000\n",
            "Epoch 2834/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2395 - accuracy: 0.9333 - val_loss: 0.4924 - val_accuracy: 0.8000\n",
            "Epoch 2835/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1289 - accuracy: 0.9667 - val_loss: 0.4907 - val_accuracy: 0.8000\n",
            "Epoch 2836/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1581 - accuracy: 0.9667 - val_loss: 0.4906 - val_accuracy: 0.8000\n",
            "Epoch 2837/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2186 - accuracy: 0.9333 - val_loss: 0.4905 - val_accuracy: 0.8000\n",
            "Epoch 2838/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2047 - accuracy: 0.9000 - val_loss: 0.4907 - val_accuracy: 0.8000\n",
            "Epoch 2839/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1797 - accuracy: 0.9667 - val_loss: 0.4908 - val_accuracy: 0.8000\n",
            "Epoch 2840/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1982 - accuracy: 0.9333 - val_loss: 0.4908 - val_accuracy: 0.7857\n",
            "Epoch 2841/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1949 - accuracy: 0.8667 - val_loss: 0.4924 - val_accuracy: 0.8000\n",
            "Epoch 2842/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1809 - accuracy: 0.9667 - val_loss: 0.4945 - val_accuracy: 0.8000\n",
            "Epoch 2843/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2057 - accuracy: 0.9333 - val_loss: 0.4970 - val_accuracy: 0.8000\n",
            "Epoch 2844/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1985 - accuracy: 0.9000 - val_loss: 0.5004 - val_accuracy: 0.7857\n",
            "Epoch 2845/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1370 - accuracy: 0.9667 - val_loss: 0.5037 - val_accuracy: 0.7857\n",
            "Epoch 2846/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1737 - accuracy: 0.9667 - val_loss: 0.5062 - val_accuracy: 0.7857\n",
            "Epoch 2847/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2368 - accuracy: 0.9000 - val_loss: 0.5089 - val_accuracy: 0.7714\n",
            "Epoch 2848/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1737 - accuracy: 0.9667 - val_loss: 0.5119 - val_accuracy: 0.7571\n",
            "Epoch 2849/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1903 - accuracy: 0.9000 - val_loss: 0.5145 - val_accuracy: 0.7571\n",
            "Epoch 2850/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2167 - accuracy: 0.9000 - val_loss: 0.5167 - val_accuracy: 0.7571\n",
            "Epoch 2851/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2941 - accuracy: 0.8333 - val_loss: 0.5180 - val_accuracy: 0.7571\n",
            "Epoch 2852/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1434 - accuracy: 0.9667 - val_loss: 0.5177 - val_accuracy: 0.7571\n",
            "Epoch 2853/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2030 - accuracy: 0.9000 - val_loss: 0.5159 - val_accuracy: 0.7571\n",
            "Epoch 2854/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2211 - accuracy: 0.9667 - val_loss: 0.5146 - val_accuracy: 0.7571\n",
            "Epoch 2855/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1681 - accuracy: 0.9333 - val_loss: 0.5131 - val_accuracy: 0.7571\n",
            "Epoch 2856/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2803 - accuracy: 0.9000 - val_loss: 0.5106 - val_accuracy: 0.7571\n",
            "Epoch 2857/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1988 - accuracy: 0.8667 - val_loss: 0.5087 - val_accuracy: 0.7571\n",
            "Epoch 2858/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2619 - accuracy: 0.8667 - val_loss: 0.5067 - val_accuracy: 0.7714\n",
            "Epoch 2859/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1949 - accuracy: 0.9667 - val_loss: 0.5047 - val_accuracy: 0.7857\n",
            "Epoch 2860/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2311 - accuracy: 0.9333 - val_loss: 0.5032 - val_accuracy: 0.7857\n",
            "Epoch 2861/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1142 - accuracy: 1.0000 - val_loss: 0.5025 - val_accuracy: 0.7857\n",
            "Epoch 2862/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1647 - accuracy: 0.9667 - val_loss: 0.5023 - val_accuracy: 0.7857\n",
            "Epoch 2863/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1867 - accuracy: 0.9333 - val_loss: 0.5016 - val_accuracy: 0.7857\n",
            "Epoch 2864/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2337 - accuracy: 0.8667 - val_loss: 0.5022 - val_accuracy: 0.7857\n",
            "Epoch 2865/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2271 - accuracy: 0.9333 - val_loss: 0.5018 - val_accuracy: 0.8000\n",
            "Epoch 2866/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1607 - accuracy: 1.0000 - val_loss: 0.5016 - val_accuracy: 0.8000\n",
            "Epoch 2867/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1589 - accuracy: 0.9667 - val_loss: 0.5009 - val_accuracy: 0.8000\n",
            "Epoch 2868/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1919 - accuracy: 0.9333 - val_loss: 0.5008 - val_accuracy: 0.8000\n",
            "Epoch 2869/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1891 - accuracy: 0.9000 - val_loss: 0.5019 - val_accuracy: 0.8000\n",
            "Epoch 2870/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1643 - accuracy: 0.9667 - val_loss: 0.5022 - val_accuracy: 0.8000\n",
            "Epoch 2871/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1884 - accuracy: 0.9333 - val_loss: 0.5013 - val_accuracy: 0.8000\n",
            "Epoch 2872/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1279 - accuracy: 0.9667 - val_loss: 0.5003 - val_accuracy: 0.8000\n",
            "Epoch 2873/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3306 - accuracy: 0.8667 - val_loss: 0.5008 - val_accuracy: 0.8000\n",
            "Epoch 2874/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1835 - accuracy: 0.9000 - val_loss: 0.5017 - val_accuracy: 0.8000\n",
            "Epoch 2875/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2285 - accuracy: 0.9333 - val_loss: 0.5025 - val_accuracy: 0.8000\n",
            "Epoch 2876/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1540 - accuracy: 1.0000 - val_loss: 0.5029 - val_accuracy: 0.7857\n",
            "Epoch 2877/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2643 - accuracy: 0.8667 - val_loss: 0.5044 - val_accuracy: 0.7857\n",
            "Epoch 2878/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.2297 - accuracy: 0.9000 - val_loss: 0.5052 - val_accuracy: 0.7857\n",
            "Epoch 2879/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1994 - accuracy: 0.9667 - val_loss: 0.5051 - val_accuracy: 0.7857\n",
            "Epoch 2880/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1771 - accuracy: 0.9667 - val_loss: 0.5052 - val_accuracy: 0.7857\n",
            "Epoch 2881/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1880 - accuracy: 0.9333 - val_loss: 0.5055 - val_accuracy: 0.8000\n",
            "Epoch 2882/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2250 - accuracy: 0.9667 - val_loss: 0.5062 - val_accuracy: 0.8000\n",
            "Epoch 2883/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1983 - accuracy: 0.9333 - val_loss: 0.5070 - val_accuracy: 0.8000\n",
            "Epoch 2884/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2545 - accuracy: 0.9333 - val_loss: 0.5082 - val_accuracy: 0.8000\n",
            "Epoch 2885/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2056 - accuracy: 0.9333 - val_loss: 0.5090 - val_accuracy: 0.8000\n",
            "Epoch 2886/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2544 - accuracy: 0.8667 - val_loss: 0.5088 - val_accuracy: 0.8000\n",
            "Epoch 2887/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1808 - accuracy: 0.9667 - val_loss: 0.5092 - val_accuracy: 0.8000\n",
            "Epoch 2888/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1986 - accuracy: 0.9000 - val_loss: 0.5104 - val_accuracy: 0.8000\n",
            "Epoch 2889/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2469 - accuracy: 0.8667 - val_loss: 0.5112 - val_accuracy: 0.8000\n",
            "Epoch 2890/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1969 - accuracy: 0.9000 - val_loss: 0.5122 - val_accuracy: 0.7857\n",
            "Epoch 2891/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2966 - accuracy: 0.8667 - val_loss: 0.5131 - val_accuracy: 0.7857\n",
            "Epoch 2892/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1757 - accuracy: 0.9667 - val_loss: 0.5139 - val_accuracy: 0.7714\n",
            "Epoch 2893/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1670 - accuracy: 0.9333 - val_loss: 0.5156 - val_accuracy: 0.7714\n",
            "Epoch 2894/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2089 - accuracy: 0.9333 - val_loss: 0.5154 - val_accuracy: 0.7714\n",
            "Epoch 2895/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1860 - accuracy: 0.9333 - val_loss: 0.5155 - val_accuracy: 0.7714\n",
            "Epoch 2896/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1694 - accuracy: 0.9333 - val_loss: 0.5160 - val_accuracy: 0.7714\n",
            "Epoch 2897/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2098 - accuracy: 0.9667 - val_loss: 0.5156 - val_accuracy: 0.7714\n",
            "Epoch 2898/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2888 - accuracy: 0.8667 - val_loss: 0.5146 - val_accuracy: 0.7714\n",
            "Epoch 2899/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.1768 - accuracy: 0.9667 - val_loss: 0.5131 - val_accuracy: 0.7714\n",
            "Epoch 2900/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2262 - accuracy: 0.9333 - val_loss: 0.5106 - val_accuracy: 0.7571\n",
            "Epoch 2901/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2013 - accuracy: 0.9333 - val_loss: 0.5085 - val_accuracy: 0.7714\n",
            "Epoch 2902/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2175 - accuracy: 0.9000 - val_loss: 0.5048 - val_accuracy: 0.7857\n",
            "Epoch 2903/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1988 - accuracy: 0.9333 - val_loss: 0.5011 - val_accuracy: 0.7857\n",
            "Epoch 2904/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1705 - accuracy: 0.9333 - val_loss: 0.4976 - val_accuracy: 0.7857\n",
            "Epoch 2905/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2108 - accuracy: 0.9667 - val_loss: 0.4953 - val_accuracy: 0.7857\n",
            "Epoch 2906/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1301 - accuracy: 1.0000 - val_loss: 0.4940 - val_accuracy: 0.7857\n",
            "Epoch 2907/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1855 - accuracy: 0.8667 - val_loss: 0.4936 - val_accuracy: 0.7857\n",
            "Epoch 2908/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2167 - accuracy: 0.9000 - val_loss: 0.4938 - val_accuracy: 0.7857\n",
            "Epoch 2909/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2547 - accuracy: 0.9000 - val_loss: 0.4931 - val_accuracy: 0.7857\n",
            "Epoch 2910/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2592 - accuracy: 0.9000 - val_loss: 0.4925 - val_accuracy: 0.7857\n",
            "Epoch 2911/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2701 - accuracy: 0.8333 - val_loss: 0.4923 - val_accuracy: 0.7857\n",
            "Epoch 2912/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2495 - accuracy: 0.8667 - val_loss: 0.4936 - val_accuracy: 0.7857\n",
            "Epoch 2913/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.1521 - accuracy: 0.9667 - val_loss: 0.4943 - val_accuracy: 0.7857\n",
            "Epoch 2914/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1800 - accuracy: 0.9667 - val_loss: 0.4959 - val_accuracy: 0.7857\n",
            "Epoch 2915/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1901 - accuracy: 0.9333 - val_loss: 0.4973 - val_accuracy: 0.7714\n",
            "Epoch 2916/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1505 - accuracy: 0.9333 - val_loss: 0.4988 - val_accuracy: 0.7714\n",
            "Epoch 2917/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2116 - accuracy: 0.9000 - val_loss: 0.5000 - val_accuracy: 0.7714\n",
            "Epoch 2918/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1842 - accuracy: 0.9000 - val_loss: 0.5022 - val_accuracy: 0.7714\n",
            "Epoch 2919/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2537 - accuracy: 0.9000 - val_loss: 0.5042 - val_accuracy: 0.7714\n",
            "Epoch 2920/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2799 - accuracy: 0.9000 - val_loss: 0.5054 - val_accuracy: 0.7714\n",
            "Epoch 2921/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2030 - accuracy: 0.9000 - val_loss: 0.5070 - val_accuracy: 0.7714\n",
            "Epoch 2922/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1733 - accuracy: 0.9000 - val_loss: 0.5084 - val_accuracy: 0.7714\n",
            "Epoch 2923/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2685 - accuracy: 0.9000 - val_loss: 0.5105 - val_accuracy: 0.7714\n",
            "Epoch 2924/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1814 - accuracy: 0.9333 - val_loss: 0.5126 - val_accuracy: 0.7714\n",
            "Epoch 2925/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2731 - accuracy: 0.9000 - val_loss: 0.5131 - val_accuracy: 0.7714\n",
            "Epoch 2926/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2030 - accuracy: 0.9000 - val_loss: 0.5131 - val_accuracy: 0.7714\n",
            "Epoch 2927/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2028 - accuracy: 0.9667 - val_loss: 0.5122 - val_accuracy: 0.7714\n",
            "Epoch 2928/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2733 - accuracy: 0.8333 - val_loss: 0.5111 - val_accuracy: 0.7714\n",
            "Epoch 2929/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1728 - accuracy: 0.9333 - val_loss: 0.5109 - val_accuracy: 0.7714\n",
            "Epoch 2930/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1711 - accuracy: 0.9667 - val_loss: 0.5100 - val_accuracy: 0.7714\n",
            "Epoch 2931/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2165 - accuracy: 0.9000 - val_loss: 0.5106 - val_accuracy: 0.7714\n",
            "Epoch 2932/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.2246 - accuracy: 0.9000 - val_loss: 0.5101 - val_accuracy: 0.7714\n",
            "Epoch 2933/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2139 - accuracy: 0.9000 - val_loss: 0.5098 - val_accuracy: 0.7714\n",
            "Epoch 2934/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1797 - accuracy: 0.9333 - val_loss: 0.5088 - val_accuracy: 0.7571\n",
            "Epoch 2935/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1742 - accuracy: 0.9333 - val_loss: 0.5079 - val_accuracy: 0.7571\n",
            "Epoch 2936/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2450 - accuracy: 0.9333 - val_loss: 0.5075 - val_accuracy: 0.7571\n",
            "Epoch 2937/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1807 - accuracy: 0.9667 - val_loss: 0.5079 - val_accuracy: 0.7571\n",
            "Epoch 2938/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1748 - accuracy: 0.9333 - val_loss: 0.5084 - val_accuracy: 0.7571\n",
            "Epoch 2939/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1991 - accuracy: 0.9000 - val_loss: 0.5082 - val_accuracy: 0.7571\n",
            "Epoch 2940/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1539 - accuracy: 0.9667 - val_loss: 0.5080 - val_accuracy: 0.7571\n",
            "Epoch 2941/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2577 - accuracy: 0.9333 - val_loss: 0.5070 - val_accuracy: 0.7571\n",
            "Epoch 2942/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2944 - accuracy: 0.8667 - val_loss: 0.5051 - val_accuracy: 0.7571\n",
            "Epoch 2943/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2134 - accuracy: 0.9667 - val_loss: 0.5032 - val_accuracy: 0.7571\n",
            "Epoch 2944/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1713 - accuracy: 0.9667 - val_loss: 0.5017 - val_accuracy: 0.7571\n",
            "Epoch 2945/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2520 - accuracy: 0.8667 - val_loss: 0.5024 - val_accuracy: 0.7571\n",
            "Epoch 2946/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2252 - accuracy: 0.9333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 2947/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2125 - accuracy: 0.9333 - val_loss: 0.5019 - val_accuracy: 0.7571\n",
            "Epoch 2948/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1700 - accuracy: 0.9667 - val_loss: 0.5023 - val_accuracy: 0.7714\n",
            "Epoch 2949/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1870 - accuracy: 0.9667 - val_loss: 0.5044 - val_accuracy: 0.7714\n",
            "Epoch 2950/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2196 - accuracy: 0.9000 - val_loss: 0.5063 - val_accuracy: 0.7714\n",
            "Epoch 2951/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2889 - accuracy: 0.8667 - val_loss: 0.5066 - val_accuracy: 0.7714\n",
            "Epoch 2952/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1862 - accuracy: 0.9333 - val_loss: 0.5060 - val_accuracy: 0.7714\n",
            "Epoch 2953/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2385 - accuracy: 0.9000 - val_loss: 0.5083 - val_accuracy: 0.7714\n",
            "Epoch 2954/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1949 - accuracy: 0.9667 - val_loss: 0.5135 - val_accuracy: 0.7714\n",
            "Epoch 2955/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2443 - accuracy: 0.9333 - val_loss: 0.5173 - val_accuracy: 0.7714\n",
            "Epoch 2956/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1752 - accuracy: 0.9667 - val_loss: 0.5199 - val_accuracy: 0.7714\n",
            "Epoch 2957/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2221 - accuracy: 0.8333 - val_loss: 0.5217 - val_accuracy: 0.7571\n",
            "Epoch 2958/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2078 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.7571\n",
            "Epoch 2959/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1818 - accuracy: 0.9667 - val_loss: 0.5234 - val_accuracy: 0.7571\n",
            "Epoch 2960/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2875 - accuracy: 0.8667 - val_loss: 0.5211 - val_accuracy: 0.7571\n",
            "Epoch 2961/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1905 - accuracy: 0.9000 - val_loss: 0.5183 - val_accuracy: 0.7714\n",
            "Epoch 2962/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2062 - accuracy: 0.9667 - val_loss: 0.5140 - val_accuracy: 0.7714\n",
            "Epoch 2963/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2535 - accuracy: 0.8667 - val_loss: 0.5086 - val_accuracy: 0.7571\n",
            "Epoch 2964/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1714 - accuracy: 0.9333 - val_loss: 0.5038 - val_accuracy: 0.7571\n",
            "Epoch 2965/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1846 - accuracy: 0.9333 - val_loss: 0.4993 - val_accuracy: 0.7857\n",
            "Epoch 2966/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2668 - accuracy: 0.8333 - val_loss: 0.4954 - val_accuracy: 0.8000\n",
            "Epoch 2967/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1727 - accuracy: 0.9333 - val_loss: 0.4920 - val_accuracy: 0.8000\n",
            "Epoch 2968/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2770 - accuracy: 0.9000 - val_loss: 0.4885 - val_accuracy: 0.8000\n",
            "Epoch 2969/4000\n",
            "1/1 [==============================] - 0s 99ms/step - loss: 0.1845 - accuracy: 0.9333 - val_loss: 0.4852 - val_accuracy: 0.8000\n",
            "Epoch 2970/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2193 - accuracy: 0.9333 - val_loss: 0.4823 - val_accuracy: 0.8000\n",
            "Epoch 2971/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2006 - accuracy: 0.9333 - val_loss: 0.4803 - val_accuracy: 0.8000\n",
            "Epoch 2972/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2759 - accuracy: 0.8667 - val_loss: 0.4788 - val_accuracy: 0.7857\n",
            "Epoch 2973/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1886 - accuracy: 0.9000 - val_loss: 0.4787 - val_accuracy: 0.7714\n",
            "Epoch 2974/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2759 - accuracy: 0.8667 - val_loss: 0.4792 - val_accuracy: 0.7714\n",
            "Epoch 2975/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2389 - accuracy: 0.8667 - val_loss: 0.4800 - val_accuracy: 0.7714\n",
            "Epoch 2976/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2162 - accuracy: 0.9000 - val_loss: 0.4811 - val_accuracy: 0.7714\n",
            "Epoch 2977/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2693 - accuracy: 0.9000 - val_loss: 0.4829 - val_accuracy: 0.7714\n",
            "Epoch 2978/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2356 - accuracy: 0.9333 - val_loss: 0.4852 - val_accuracy: 0.7714\n",
            "Epoch 2979/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1702 - accuracy: 0.9333 - val_loss: 0.4878 - val_accuracy: 0.7857\n",
            "Epoch 2980/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2071 - accuracy: 0.9333 - val_loss: 0.4920 - val_accuracy: 0.7857\n",
            "Epoch 2981/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2268 - accuracy: 0.9000 - val_loss: 0.4950 - val_accuracy: 0.7857\n",
            "Epoch 2982/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2055 - accuracy: 0.9333 - val_loss: 0.4977 - val_accuracy: 0.7857\n",
            "Epoch 2983/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1748 - accuracy: 0.9667 - val_loss: 0.5003 - val_accuracy: 0.7857\n",
            "Epoch 2984/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1940 - accuracy: 0.9333 - val_loss: 0.5019 - val_accuracy: 0.7857\n",
            "Epoch 2985/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2490 - accuracy: 0.9333 - val_loss: 0.5047 - val_accuracy: 0.7857\n",
            "Epoch 2986/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1999 - accuracy: 0.9000 - val_loss: 0.5077 - val_accuracy: 0.7571\n",
            "Epoch 2987/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1817 - accuracy: 0.9667 - val_loss: 0.5100 - val_accuracy: 0.7571\n",
            "Epoch 2988/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2497 - accuracy: 0.9667 - val_loss: 0.5126 - val_accuracy: 0.7571\n",
            "Epoch 2989/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2045 - accuracy: 0.9000 - val_loss: 0.5158 - val_accuracy: 0.7714\n",
            "Epoch 2990/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2473 - accuracy: 0.9000 - val_loss: 0.5191 - val_accuracy: 0.7714\n",
            "Epoch 2991/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2145 - accuracy: 0.9333 - val_loss: 0.5213 - val_accuracy: 0.7714\n",
            "Epoch 2992/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1917 - accuracy: 0.9333 - val_loss: 0.5217 - val_accuracy: 0.7714\n",
            "Epoch 2993/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1889 - accuracy: 0.9333 - val_loss: 0.5210 - val_accuracy: 0.7714\n",
            "Epoch 2994/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1988 - accuracy: 0.9000 - val_loss: 0.5192 - val_accuracy: 0.7714\n",
            "Epoch 2995/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1783 - accuracy: 0.9667 - val_loss: 0.5183 - val_accuracy: 0.7714\n",
            "Epoch 2996/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2248 - accuracy: 0.9333 - val_loss: 0.5186 - val_accuracy: 0.7714\n",
            "Epoch 2997/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1781 - accuracy: 0.9667 - val_loss: 0.5200 - val_accuracy: 0.7714\n",
            "Epoch 2998/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1545 - accuracy: 0.9667 - val_loss: 0.5208 - val_accuracy: 0.7714\n",
            "Epoch 2999/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2343 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.7714\n",
            "Epoch 3000/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2230 - accuracy: 0.9333 - val_loss: 0.5232 - val_accuracy: 0.7714\n",
            "Epoch 3001/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2200 - accuracy: 0.9333 - val_loss: 0.5226 - val_accuracy: 0.7714\n",
            "Epoch 3002/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2208 - accuracy: 0.9000 - val_loss: 0.5208 - val_accuracy: 0.7714\n",
            "Epoch 3003/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2182 - accuracy: 0.9000 - val_loss: 0.5195 - val_accuracy: 0.7857\n",
            "Epoch 3004/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2462 - accuracy: 0.8333 - val_loss: 0.5174 - val_accuracy: 0.7857\n",
            "Epoch 3005/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1433 - accuracy: 0.9667 - val_loss: 0.5168 - val_accuracy: 0.7857\n",
            "Epoch 3006/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1698 - accuracy: 0.9667 - val_loss: 0.5165 - val_accuracy: 0.7714\n",
            "Epoch 3007/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2375 - accuracy: 0.9000 - val_loss: 0.5168 - val_accuracy: 0.7714\n",
            "Epoch 3008/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2456 - accuracy: 0.9333 - val_loss: 0.5158 - val_accuracy: 0.7714\n",
            "Epoch 3009/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1952 - accuracy: 0.9333 - val_loss: 0.5136 - val_accuracy: 0.7857\n",
            "Epoch 3010/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2065 - accuracy: 0.9333 - val_loss: 0.5128 - val_accuracy: 0.7857\n",
            "Epoch 3011/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2887 - accuracy: 0.9000 - val_loss: 0.5111 - val_accuracy: 0.7857\n",
            "Epoch 3012/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1479 - accuracy: 0.9333 - val_loss: 0.5079 - val_accuracy: 0.7857\n",
            "Epoch 3013/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1894 - accuracy: 0.9333 - val_loss: 0.5047 - val_accuracy: 0.7857\n",
            "Epoch 3014/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.2035 - accuracy: 0.9333 - val_loss: 0.5012 - val_accuracy: 0.7857\n",
            "Epoch 3015/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1935 - accuracy: 0.9333 - val_loss: 0.4964 - val_accuracy: 0.7857\n",
            "Epoch 3016/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1648 - accuracy: 0.9667 - val_loss: 0.4927 - val_accuracy: 0.7857\n",
            "Epoch 3017/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1697 - accuracy: 0.9667 - val_loss: 0.4889 - val_accuracy: 0.7571\n",
            "Epoch 3018/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1738 - accuracy: 0.9000 - val_loss: 0.4860 - val_accuracy: 0.7714\n",
            "Epoch 3019/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1363 - accuracy: 1.0000 - val_loss: 0.4838 - val_accuracy: 0.7857\n",
            "Epoch 3020/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2076 - accuracy: 0.9333 - val_loss: 0.4818 - val_accuracy: 0.7857\n",
            "Epoch 3021/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2498 - accuracy: 0.8333 - val_loss: 0.4808 - val_accuracy: 0.7857\n",
            "Epoch 3022/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2012 - accuracy: 0.9333 - val_loss: 0.4812 - val_accuracy: 0.7714\n",
            "Epoch 3023/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2287 - accuracy: 0.8667 - val_loss: 0.4831 - val_accuracy: 0.7571\n",
            "Epoch 3024/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1779 - accuracy: 0.9667 - val_loss: 0.4870 - val_accuracy: 0.7857\n",
            "Epoch 3025/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1783 - accuracy: 0.9333 - val_loss: 0.4913 - val_accuracy: 0.7857\n",
            "Epoch 3026/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2874 - accuracy: 0.8667 - val_loss: 0.4949 - val_accuracy: 0.7857\n",
            "Epoch 3027/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1698 - accuracy: 0.9667 - val_loss: 0.4977 - val_accuracy: 0.7857\n",
            "Epoch 3028/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1470 - accuracy: 0.9667 - val_loss: 0.5005 - val_accuracy: 0.8000\n",
            "Epoch 3029/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2033 - accuracy: 0.9000 - val_loss: 0.5021 - val_accuracy: 0.8000\n",
            "Epoch 3030/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2464 - accuracy: 0.9000 - val_loss: 0.5040 - val_accuracy: 0.8000\n",
            "Epoch 3031/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1894 - accuracy: 0.9667 - val_loss: 0.5053 - val_accuracy: 0.8000\n",
            "Epoch 3032/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1919 - accuracy: 0.9333 - val_loss: 0.5059 - val_accuracy: 0.8000\n",
            "Epoch 3033/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2340 - accuracy: 0.9000 - val_loss: 0.5071 - val_accuracy: 0.8000\n",
            "Epoch 3034/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2491 - accuracy: 0.9000 - val_loss: 0.5081 - val_accuracy: 0.8000\n",
            "Epoch 3035/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2329 - accuracy: 0.9333 - val_loss: 0.5092 - val_accuracy: 0.8000\n",
            "Epoch 3036/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1758 - accuracy: 0.9667 - val_loss: 0.5109 - val_accuracy: 0.8000\n",
            "Epoch 3037/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1698 - accuracy: 0.9667 - val_loss: 0.5125 - val_accuracy: 0.8000\n",
            "Epoch 3038/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1826 - accuracy: 0.9000 - val_loss: 0.5132 - val_accuracy: 0.8000\n",
            "Epoch 3039/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1595 - accuracy: 0.9667 - val_loss: 0.5151 - val_accuracy: 0.8000\n",
            "Epoch 3040/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1995 - accuracy: 0.9333 - val_loss: 0.5166 - val_accuracy: 0.7857\n",
            "Epoch 3041/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2437 - accuracy: 0.8667 - val_loss: 0.5176 - val_accuracy: 0.7857\n",
            "Epoch 3042/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1572 - accuracy: 0.9667 - val_loss: 0.5186 - val_accuracy: 0.7857\n",
            "Epoch 3043/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2105 - accuracy: 0.9000 - val_loss: 0.5179 - val_accuracy: 0.7857\n",
            "Epoch 3044/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1728 - accuracy: 0.9667 - val_loss: 0.5182 - val_accuracy: 0.7714\n",
            "Epoch 3045/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2612 - accuracy: 0.9333 - val_loss: 0.5172 - val_accuracy: 0.7714\n",
            "Epoch 3046/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2107 - accuracy: 0.9333 - val_loss: 0.5163 - val_accuracy: 0.7857\n",
            "Epoch 3047/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2160 - accuracy: 0.9000 - val_loss: 0.5162 - val_accuracy: 0.7857\n",
            "Epoch 3048/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.2068 - accuracy: 0.9000 - val_loss: 0.5152 - val_accuracy: 0.7857\n",
            "Epoch 3049/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2714 - accuracy: 0.8333 - val_loss: 0.5142 - val_accuracy: 0.8000\n",
            "Epoch 3050/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1820 - accuracy: 0.9667 - val_loss: 0.5127 - val_accuracy: 0.8000\n",
            "Epoch 3051/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2048 - accuracy: 0.9000 - val_loss: 0.5111 - val_accuracy: 0.8000\n",
            "Epoch 3052/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1719 - accuracy: 0.9333 - val_loss: 0.5106 - val_accuracy: 0.8000\n",
            "Epoch 3053/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1487 - accuracy: 0.9667 - val_loss: 0.5097 - val_accuracy: 0.8000\n",
            "Epoch 3054/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2719 - accuracy: 0.9333 - val_loss: 0.5097 - val_accuracy: 0.8000\n",
            "Epoch 3055/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2032 - accuracy: 0.9333 - val_loss: 0.5106 - val_accuracy: 0.8000\n",
            "Epoch 3056/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2029 - accuracy: 0.9000 - val_loss: 0.5132 - val_accuracy: 0.8000\n",
            "Epoch 3057/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1798 - accuracy: 0.9667 - val_loss: 0.5162 - val_accuracy: 0.7857\n",
            "Epoch 3058/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2536 - accuracy: 0.8667 - val_loss: 0.5186 - val_accuracy: 0.7857\n",
            "Epoch 3059/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2780 - accuracy: 0.8667 - val_loss: 0.5207 - val_accuracy: 0.7714\n",
            "Epoch 3060/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1986 - accuracy: 0.9333 - val_loss: 0.5217 - val_accuracy: 0.7714\n",
            "Epoch 3061/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1943 - accuracy: 0.9333 - val_loss: 0.5219 - val_accuracy: 0.7714\n",
            "Epoch 3062/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1884 - accuracy: 0.9333 - val_loss: 0.5221 - val_accuracy: 0.7714\n",
            "Epoch 3063/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2806 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.7714\n",
            "Epoch 3064/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2306 - accuracy: 0.9000 - val_loss: 0.5217 - val_accuracy: 0.7714\n",
            "Epoch 3065/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1903 - accuracy: 0.9000 - val_loss: 0.5204 - val_accuracy: 0.7714\n",
            "Epoch 3066/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1850 - accuracy: 0.9667 - val_loss: 0.5202 - val_accuracy: 0.7714\n",
            "Epoch 3067/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1557 - accuracy: 0.9667 - val_loss: 0.5209 - val_accuracy: 0.7714\n",
            "Epoch 3068/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2448 - accuracy: 0.9000 - val_loss: 0.5205 - val_accuracy: 0.7714\n",
            "Epoch 3069/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1763 - accuracy: 0.9667 - val_loss: 0.5212 - val_accuracy: 0.7714\n",
            "Epoch 3070/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2102 - accuracy: 0.9667 - val_loss: 0.5215 - val_accuracy: 0.7714\n",
            "Epoch 3071/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2019 - accuracy: 0.9667 - val_loss: 0.5221 - val_accuracy: 0.7714\n",
            "Epoch 3072/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1851 - accuracy: 0.9333 - val_loss: 0.5231 - val_accuracy: 0.7714\n",
            "Epoch 3073/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2105 - accuracy: 0.9000 - val_loss: 0.5259 - val_accuracy: 0.7714\n",
            "Epoch 3074/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2166 - accuracy: 0.9333 - val_loss: 0.5279 - val_accuracy: 0.7714\n",
            "Epoch 3075/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2018 - accuracy: 0.9000 - val_loss: 0.5294 - val_accuracy: 0.7714\n",
            "Epoch 3076/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2016 - accuracy: 0.9333 - val_loss: 0.5309 - val_accuracy: 0.7714\n",
            "Epoch 3077/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2542 - accuracy: 0.9333 - val_loss: 0.5333 - val_accuracy: 0.7714\n",
            "Epoch 3078/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1806 - accuracy: 0.9667 - val_loss: 0.5337 - val_accuracy: 0.7714\n",
            "Epoch 3079/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2486 - accuracy: 0.9000 - val_loss: 0.5339 - val_accuracy: 0.7714\n",
            "Epoch 3080/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2218 - accuracy: 0.9333 - val_loss: 0.5325 - val_accuracy: 0.7714\n",
            "Epoch 3081/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2205 - accuracy: 0.9333 - val_loss: 0.5294 - val_accuracy: 0.7714\n",
            "Epoch 3082/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1564 - accuracy: 0.9667 - val_loss: 0.5261 - val_accuracy: 0.7714\n",
            "Epoch 3083/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1181 - accuracy: 1.0000 - val_loss: 0.5223 - val_accuracy: 0.7714\n",
            "Epoch 3084/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1622 - accuracy: 0.9667 - val_loss: 0.5201 - val_accuracy: 0.7714\n",
            "Epoch 3085/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1592 - accuracy: 0.9667 - val_loss: 0.5172 - val_accuracy: 0.7714\n",
            "Epoch 3086/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2433 - accuracy: 0.9000 - val_loss: 0.5144 - val_accuracy: 0.7857\n",
            "Epoch 3087/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2607 - accuracy: 0.9333 - val_loss: 0.5130 - val_accuracy: 0.8000\n",
            "Epoch 3088/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2365 - accuracy: 0.8667 - val_loss: 0.5120 - val_accuracy: 0.8000\n",
            "Epoch 3089/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1777 - accuracy: 0.9000 - val_loss: 0.5124 - val_accuracy: 0.8000\n",
            "Epoch 3090/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1874 - accuracy: 0.9000 - val_loss: 0.5122 - val_accuracy: 0.8000\n",
            "Epoch 3091/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1825 - accuracy: 0.9000 - val_loss: 0.5121 - val_accuracy: 0.8000\n",
            "Epoch 3092/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1760 - accuracy: 0.9667 - val_loss: 0.5115 - val_accuracy: 0.8000\n",
            "Epoch 3093/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1579 - accuracy: 0.9667 - val_loss: 0.5114 - val_accuracy: 0.8000\n",
            "Epoch 3094/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2426 - accuracy: 0.9000 - val_loss: 0.5114 - val_accuracy: 0.8000\n",
            "Epoch 3095/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2204 - accuracy: 0.9000 - val_loss: 0.5097 - val_accuracy: 0.7857\n",
            "Epoch 3096/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1772 - accuracy: 0.9333 - val_loss: 0.5090 - val_accuracy: 0.7857\n",
            "Epoch 3097/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1567 - accuracy: 0.9333 - val_loss: 0.5082 - val_accuracy: 0.7857\n",
            "Epoch 3098/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1724 - accuracy: 0.9667 - val_loss: 0.5069 - val_accuracy: 0.7857\n",
            "Epoch 3099/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1925 - accuracy: 0.9000 - val_loss: 0.5049 - val_accuracy: 0.7857\n",
            "Epoch 3100/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2306 - accuracy: 0.9333 - val_loss: 0.5013 - val_accuracy: 0.8000\n",
            "Epoch 3101/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.1777 - accuracy: 0.9000 - val_loss: 0.4978 - val_accuracy: 0.8000\n",
            "Epoch 3102/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2172 - accuracy: 0.9667 - val_loss: 0.4958 - val_accuracy: 0.8000\n",
            "Epoch 3103/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2460 - accuracy: 0.9333 - val_loss: 0.4954 - val_accuracy: 0.8000\n",
            "Epoch 3104/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2525 - accuracy: 0.9333 - val_loss: 0.4949 - val_accuracy: 0.7857\n",
            "Epoch 3105/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2334 - accuracy: 0.9000 - val_loss: 0.4942 - val_accuracy: 0.7857\n",
            "Epoch 3106/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1667 - accuracy: 0.9333 - val_loss: 0.4932 - val_accuracy: 0.7857\n",
            "Epoch 3107/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1557 - accuracy: 0.9000 - val_loss: 0.4922 - val_accuracy: 0.8000\n",
            "Epoch 3108/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1549 - accuracy: 1.0000 - val_loss: 0.4909 - val_accuracy: 0.8000\n",
            "Epoch 3109/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2129 - accuracy: 0.9333 - val_loss: 0.4898 - val_accuracy: 0.8000\n",
            "Epoch 3110/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2138 - accuracy: 0.9333 - val_loss: 0.4890 - val_accuracy: 0.8000\n",
            "Epoch 3111/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2603 - accuracy: 0.9000 - val_loss: 0.4882 - val_accuracy: 0.8000\n",
            "Epoch 3112/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1628 - accuracy: 0.9667 - val_loss: 0.4878 - val_accuracy: 0.8000\n",
            "Epoch 3113/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1684 - accuracy: 0.9667 - val_loss: 0.4876 - val_accuracy: 0.8000\n",
            "Epoch 3114/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2559 - accuracy: 0.9333 - val_loss: 0.4895 - val_accuracy: 0.8000\n",
            "Epoch 3115/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1795 - accuracy: 0.9667 - val_loss: 0.4926 - val_accuracy: 0.8000\n",
            "Epoch 3116/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.3025 - accuracy: 0.8667 - val_loss: 0.4971 - val_accuracy: 0.7857\n",
            "Epoch 3117/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1462 - accuracy: 0.9667 - val_loss: 0.5016 - val_accuracy: 0.7857\n",
            "Epoch 3118/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2682 - accuracy: 0.9000 - val_loss: 0.5059 - val_accuracy: 0.7714\n",
            "Epoch 3119/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2321 - accuracy: 0.9000 - val_loss: 0.5100 - val_accuracy: 0.7571\n",
            "Epoch 3120/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1370 - accuracy: 1.0000 - val_loss: 0.5139 - val_accuracy: 0.7571\n",
            "Epoch 3121/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1842 - accuracy: 0.9667 - val_loss: 0.5180 - val_accuracy: 0.7571\n",
            "Epoch 3122/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1931 - accuracy: 0.9333 - val_loss: 0.5212 - val_accuracy: 0.7571\n",
            "Epoch 3123/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2003 - accuracy: 0.9000 - val_loss: 0.5233 - val_accuracy: 0.7571\n",
            "Epoch 3124/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2006 - accuracy: 0.9000 - val_loss: 0.5227 - val_accuracy: 0.7571\n",
            "Epoch 3125/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2580 - accuracy: 0.8333 - val_loss: 0.5208 - val_accuracy: 0.7571\n",
            "Epoch 3126/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2006 - accuracy: 0.9333 - val_loss: 0.5195 - val_accuracy: 0.7571\n",
            "Epoch 3127/4000\n",
            "1/1 [==============================] - 0s 39ms/step - loss: 0.2294 - accuracy: 0.8333 - val_loss: 0.5194 - val_accuracy: 0.7571\n",
            "Epoch 3128/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.2398 - accuracy: 0.8333 - val_loss: 0.5182 - val_accuracy: 0.7571\n",
            "Epoch 3129/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2779 - accuracy: 0.8667 - val_loss: 0.5154 - val_accuracy: 0.7571\n",
            "Epoch 3130/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1502 - accuracy: 0.9333 - val_loss: 0.5140 - val_accuracy: 0.7571\n",
            "Epoch 3131/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2410 - accuracy: 0.8667 - val_loss: 0.5119 - val_accuracy: 0.7571\n",
            "Epoch 3132/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1890 - accuracy: 0.9333 - val_loss: 0.5087 - val_accuracy: 0.7571\n",
            "Epoch 3133/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2138 - accuracy: 0.9000 - val_loss: 0.5067 - val_accuracy: 0.7571\n",
            "Epoch 3134/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1433 - accuracy: 0.9667 - val_loss: 0.5053 - val_accuracy: 0.7571\n",
            "Epoch 3135/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1815 - accuracy: 0.9667 - val_loss: 0.5033 - val_accuracy: 0.7571\n",
            "Epoch 3136/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1881 - accuracy: 0.9667 - val_loss: 0.5022 - val_accuracy: 0.7571\n",
            "Epoch 3137/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2381 - accuracy: 0.9333 - val_loss: 0.5020 - val_accuracy: 0.7571\n",
            "Epoch 3138/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1835 - accuracy: 0.9667 - val_loss: 0.5014 - val_accuracy: 0.7571\n",
            "Epoch 3139/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1450 - accuracy: 0.9667 - val_loss: 0.5013 - val_accuracy: 0.7571\n",
            "Epoch 3140/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2822 - accuracy: 0.8333 - val_loss: 0.5014 - val_accuracy: 0.7571\n",
            "Epoch 3141/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2432 - accuracy: 0.9333 - val_loss: 0.5004 - val_accuracy: 0.7714\n",
            "Epoch 3142/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2123 - accuracy: 0.8667 - val_loss: 0.5000 - val_accuracy: 0.7714\n",
            "Epoch 3143/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2374 - accuracy: 0.9000 - val_loss: 0.4970 - val_accuracy: 0.7714\n",
            "Epoch 3144/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1996 - accuracy: 0.9000 - val_loss: 0.4953 - val_accuracy: 0.7714\n",
            "Epoch 3145/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2758 - accuracy: 0.8667 - val_loss: 0.4956 - val_accuracy: 0.7714\n",
            "Epoch 3146/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1473 - accuracy: 0.9667 - val_loss: 0.4963 - val_accuracy: 0.7714\n",
            "Epoch 3147/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2675 - accuracy: 0.9000 - val_loss: 0.4962 - val_accuracy: 0.7714\n",
            "Epoch 3148/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2280 - accuracy: 0.9333 - val_loss: 0.4967 - val_accuracy: 0.7857\n",
            "Epoch 3149/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1922 - accuracy: 0.9333 - val_loss: 0.4981 - val_accuracy: 0.7857\n",
            "Epoch 3150/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2037 - accuracy: 0.9000 - val_loss: 0.4999 - val_accuracy: 0.7857\n",
            "Epoch 3151/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1707 - accuracy: 0.9333 - val_loss: 0.5013 - val_accuracy: 0.7714\n",
            "Epoch 3152/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2012 - accuracy: 0.9333 - val_loss: 0.5032 - val_accuracy: 0.7714\n",
            "Epoch 3153/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1779 - accuracy: 0.9333 - val_loss: 0.5056 - val_accuracy: 0.7714\n",
            "Epoch 3154/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2207 - accuracy: 0.9000 - val_loss: 0.5068 - val_accuracy: 0.7714\n",
            "Epoch 3155/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1518 - accuracy: 0.9667 - val_loss: 0.5084 - val_accuracy: 0.7714\n",
            "Epoch 3156/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2663 - accuracy: 0.9333 - val_loss: 0.5094 - val_accuracy: 0.7714\n",
            "Epoch 3157/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2835 - accuracy: 0.8667 - val_loss: 0.5086 - val_accuracy: 0.7714\n",
            "Epoch 3158/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1834 - accuracy: 0.9667 - val_loss: 0.5072 - val_accuracy: 0.7714\n",
            "Epoch 3159/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1782 - accuracy: 0.9333 - val_loss: 0.5055 - val_accuracy: 0.7714\n",
            "Epoch 3160/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2077 - accuracy: 0.9000 - val_loss: 0.5047 - val_accuracy: 0.7714\n",
            "Epoch 3161/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2284 - accuracy: 0.8667 - val_loss: 0.5037 - val_accuracy: 0.7714\n",
            "Epoch 3162/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1543 - accuracy: 0.9333 - val_loss: 0.5035 - val_accuracy: 0.7714\n",
            "Epoch 3163/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1906 - accuracy: 0.9667 - val_loss: 0.5026 - val_accuracy: 0.7714\n",
            "Epoch 3164/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1720 - accuracy: 0.9333 - val_loss: 0.5027 - val_accuracy: 0.7714\n",
            "Epoch 3165/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1850 - accuracy: 0.9333 - val_loss: 0.5018 - val_accuracy: 0.7714\n",
            "Epoch 3166/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1787 - accuracy: 0.9667 - val_loss: 0.5012 - val_accuracy: 0.7714\n",
            "Epoch 3167/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2511 - accuracy: 0.9333 - val_loss: 0.4990 - val_accuracy: 0.7714\n",
            "Epoch 3168/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1766 - accuracy: 0.9333 - val_loss: 0.4974 - val_accuracy: 0.7857\n",
            "Epoch 3169/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2241 - accuracy: 0.8667 - val_loss: 0.4966 - val_accuracy: 0.7857\n",
            "Epoch 3170/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1676 - accuracy: 0.9333 - val_loss: 0.4957 - val_accuracy: 0.7857\n",
            "Epoch 3171/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2517 - accuracy: 0.9333 - val_loss: 0.4937 - val_accuracy: 0.7857\n",
            "Epoch 3172/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1634 - accuracy: 0.9000 - val_loss: 0.4923 - val_accuracy: 0.7857\n",
            "Epoch 3173/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1952 - accuracy: 0.9333 - val_loss: 0.4914 - val_accuracy: 0.7857\n",
            "Epoch 3174/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.2227 - accuracy: 0.9000 - val_loss: 0.4889 - val_accuracy: 0.7857\n",
            "Epoch 3175/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2257 - accuracy: 0.9333 - val_loss: 0.4865 - val_accuracy: 0.7857\n",
            "Epoch 3176/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2040 - accuracy: 0.9333 - val_loss: 0.4839 - val_accuracy: 0.7857\n",
            "Epoch 3177/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2385 - accuracy: 0.8667 - val_loss: 0.4825 - val_accuracy: 0.8000\n",
            "Epoch 3178/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1442 - accuracy: 0.9667 - val_loss: 0.4820 - val_accuracy: 0.8000\n",
            "Epoch 3179/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2044 - accuracy: 0.9000 - val_loss: 0.4827 - val_accuracy: 0.8000\n",
            "Epoch 3180/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1588 - accuracy: 1.0000 - val_loss: 0.4838 - val_accuracy: 0.8000\n",
            "Epoch 3181/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1560 - accuracy: 0.9667 - val_loss: 0.4857 - val_accuracy: 0.8000\n",
            "Epoch 3182/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1702 - accuracy: 0.9333 - val_loss: 0.4882 - val_accuracy: 0.8000\n",
            "Epoch 3183/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1567 - accuracy: 0.9000 - val_loss: 0.4906 - val_accuracy: 0.8000\n",
            "Epoch 3184/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1913 - accuracy: 0.9333 - val_loss: 0.4933 - val_accuracy: 0.8000\n",
            "Epoch 3185/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1523 - accuracy: 0.9667 - val_loss: 0.4955 - val_accuracy: 0.8000\n",
            "Epoch 3186/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1284 - accuracy: 0.9667 - val_loss: 0.4975 - val_accuracy: 0.8000\n",
            "Epoch 3187/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2261 - accuracy: 0.9667 - val_loss: 0.4994 - val_accuracy: 0.8000\n",
            "Epoch 3188/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1722 - accuracy: 0.9333 - val_loss: 0.5013 - val_accuracy: 0.8000\n",
            "Epoch 3189/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2036 - accuracy: 0.9667 - val_loss: 0.5029 - val_accuracy: 0.8000\n",
            "Epoch 3190/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2429 - accuracy: 0.8667 - val_loss: 0.5045 - val_accuracy: 0.8000\n",
            "Epoch 3191/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1582 - accuracy: 0.9667 - val_loss: 0.5056 - val_accuracy: 0.8000\n",
            "Epoch 3192/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1633 - accuracy: 0.9000 - val_loss: 0.5071 - val_accuracy: 0.8000\n",
            "Epoch 3193/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1551 - accuracy: 0.9333 - val_loss: 0.5098 - val_accuracy: 0.8000\n",
            "Epoch 3194/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2450 - accuracy: 0.9000 - val_loss: 0.5120 - val_accuracy: 0.8000\n",
            "Epoch 3195/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1416 - accuracy: 1.0000 - val_loss: 0.5145 - val_accuracy: 0.7857\n",
            "Epoch 3196/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1716 - accuracy: 0.9667 - val_loss: 0.5170 - val_accuracy: 0.7857\n",
            "Epoch 3197/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1234 - accuracy: 0.9667 - val_loss: 0.5181 - val_accuracy: 0.7857\n",
            "Epoch 3198/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1886 - accuracy: 0.9333 - val_loss: 0.5183 - val_accuracy: 0.7857\n",
            "Epoch 3199/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1594 - accuracy: 0.9333 - val_loss: 0.5184 - val_accuracy: 0.7857\n",
            "Epoch 3200/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.1963 - accuracy: 0.9000 - val_loss: 0.5173 - val_accuracy: 0.7857\n",
            "Epoch 3201/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1588 - accuracy: 0.9667 - val_loss: 0.5159 - val_accuracy: 0.8000\n",
            "Epoch 3202/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1675 - accuracy: 0.9000 - val_loss: 0.5143 - val_accuracy: 0.8000\n",
            "Epoch 3203/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1566 - accuracy: 0.9667 - val_loss: 0.5130 - val_accuracy: 0.8000\n",
            "Epoch 3204/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1640 - accuracy: 0.9333 - val_loss: 0.5107 - val_accuracy: 0.8000\n",
            "Epoch 3205/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2868 - accuracy: 0.9000 - val_loss: 0.5104 - val_accuracy: 0.8000\n",
            "Epoch 3206/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2118 - accuracy: 0.9333 - val_loss: 0.5103 - val_accuracy: 0.8000\n",
            "Epoch 3207/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2043 - accuracy: 0.9000 - val_loss: 0.5109 - val_accuracy: 0.8000\n",
            "Epoch 3208/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1473 - accuracy: 0.9667 - val_loss: 0.5108 - val_accuracy: 0.8000\n",
            "Epoch 3209/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2362 - accuracy: 0.9000 - val_loss: 0.5112 - val_accuracy: 0.8000\n",
            "Epoch 3210/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2736 - accuracy: 0.8333 - val_loss: 0.5116 - val_accuracy: 0.8000\n",
            "Epoch 3211/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1801 - accuracy: 0.9667 - val_loss: 0.5121 - val_accuracy: 0.8000\n",
            "Epoch 3212/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1526 - accuracy: 0.9667 - val_loss: 0.5137 - val_accuracy: 0.7857\n",
            "Epoch 3213/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1704 - accuracy: 0.9333 - val_loss: 0.5154 - val_accuracy: 0.7857\n",
            "Epoch 3214/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1513 - accuracy: 0.9667 - val_loss: 0.5173 - val_accuracy: 0.7714\n",
            "Epoch 3215/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1955 - accuracy: 0.9333 - val_loss: 0.5178 - val_accuracy: 0.7714\n",
            "Epoch 3216/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.2279 - accuracy: 0.9000 - val_loss: 0.5173 - val_accuracy: 0.7714\n",
            "Epoch 3217/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1760 - accuracy: 0.9667 - val_loss: 0.5166 - val_accuracy: 0.7714\n",
            "Epoch 3218/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1494 - accuracy: 0.9667 - val_loss: 0.5162 - val_accuracy: 0.7714\n",
            "Epoch 3219/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1623 - accuracy: 0.9667 - val_loss: 0.5141 - val_accuracy: 0.7714\n",
            "Epoch 3220/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2255 - accuracy: 0.9000 - val_loss: 0.5108 - val_accuracy: 0.7714\n",
            "Epoch 3221/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1842 - accuracy: 0.9000 - val_loss: 0.5078 - val_accuracy: 0.7714\n",
            "Epoch 3222/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2665 - accuracy: 0.8667 - val_loss: 0.5044 - val_accuracy: 0.7857\n",
            "Epoch 3223/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1732 - accuracy: 1.0000 - val_loss: 0.5016 - val_accuracy: 0.7857\n",
            "Epoch 3224/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.1891 - accuracy: 0.9333 - val_loss: 0.4985 - val_accuracy: 0.7857\n",
            "Epoch 3225/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2573 - accuracy: 0.9000 - val_loss: 0.4953 - val_accuracy: 0.7857\n",
            "Epoch 3226/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.2250 - accuracy: 0.9333 - val_loss: 0.4918 - val_accuracy: 0.8000\n",
            "Epoch 3227/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1920 - accuracy: 0.9333 - val_loss: 0.4894 - val_accuracy: 0.7857\n",
            "Epoch 3228/4000\n",
            "1/1 [==============================] - 0s 78ms/step - loss: 0.3525 - accuracy: 0.7667 - val_loss: 0.4872 - val_accuracy: 0.7857\n",
            "Epoch 3229/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1820 - accuracy: 0.9667 - val_loss: 0.4864 - val_accuracy: 0.8000\n",
            "Epoch 3230/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1590 - accuracy: 0.9333 - val_loss: 0.4863 - val_accuracy: 0.8000\n",
            "Epoch 3231/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1916 - accuracy: 0.9667 - val_loss: 0.4868 - val_accuracy: 0.8000\n",
            "Epoch 3232/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.3425 - accuracy: 0.8333 - val_loss: 0.4888 - val_accuracy: 0.7857\n",
            "Epoch 3233/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1265 - accuracy: 0.9333 - val_loss: 0.4915 - val_accuracy: 0.7857\n",
            "Epoch 3234/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2514 - accuracy: 0.8667 - val_loss: 0.4933 - val_accuracy: 0.8000\n",
            "Epoch 3235/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1053 - accuracy: 0.9667 - val_loss: 0.4950 - val_accuracy: 0.8000\n",
            "Epoch 3236/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2322 - accuracy: 0.9000 - val_loss: 0.4971 - val_accuracy: 0.8000\n",
            "Epoch 3237/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2037 - accuracy: 0.9333 - val_loss: 0.4996 - val_accuracy: 0.7857\n",
            "Epoch 3238/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.1966 - accuracy: 0.9333 - val_loss: 0.5035 - val_accuracy: 0.7857\n",
            "Epoch 3239/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1706 - accuracy: 0.9667 - val_loss: 0.5071 - val_accuracy: 0.7857\n",
            "Epoch 3240/4000\n",
            "1/1 [==============================] - 0s 89ms/step - loss: 0.1845 - accuracy: 0.9333 - val_loss: 0.5112 - val_accuracy: 0.7857\n",
            "Epoch 3241/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2367 - accuracy: 0.9000 - val_loss: 0.5139 - val_accuracy: 0.7714\n",
            "Epoch 3242/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1598 - accuracy: 0.9667 - val_loss: 0.5163 - val_accuracy: 0.7714\n",
            "Epoch 3243/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1845 - accuracy: 0.9667 - val_loss: 0.5176 - val_accuracy: 0.7714\n",
            "Epoch 3244/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1892 - accuracy: 0.9333 - val_loss: 0.5197 - val_accuracy: 0.7714\n",
            "Epoch 3245/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2543 - accuracy: 0.9000 - val_loss: 0.5213 - val_accuracy: 0.7714\n",
            "Epoch 3246/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1458 - accuracy: 0.9000 - val_loss: 0.5234 - val_accuracy: 0.7714\n",
            "Epoch 3247/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1727 - accuracy: 0.9667 - val_loss: 0.5253 - val_accuracy: 0.7714\n",
            "Epoch 3248/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2247 - accuracy: 0.9333 - val_loss: 0.5268 - val_accuracy: 0.7714\n",
            "Epoch 3249/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.1720 - accuracy: 0.9333 - val_loss: 0.5282 - val_accuracy: 0.7714\n",
            "Epoch 3250/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1762 - accuracy: 0.9333 - val_loss: 0.5284 - val_accuracy: 0.7714\n",
            "Epoch 3251/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1578 - accuracy: 0.9667 - val_loss: 0.5291 - val_accuracy: 0.7714\n",
            "Epoch 3252/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1967 - accuracy: 0.9333 - val_loss: 0.5296 - val_accuracy: 0.7571\n",
            "Epoch 3253/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2300 - accuracy: 0.9000 - val_loss: 0.5296 - val_accuracy: 0.7571\n",
            "Epoch 3254/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1810 - accuracy: 0.9333 - val_loss: 0.5301 - val_accuracy: 0.7571\n",
            "Epoch 3255/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.1928 - accuracy: 0.9667 - val_loss: 0.5310 - val_accuracy: 0.7571\n",
            "Epoch 3256/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1610 - accuracy: 0.9667 - val_loss: 0.5312 - val_accuracy: 0.7571\n",
            "Epoch 3257/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1469 - accuracy: 0.9333 - val_loss: 0.5312 - val_accuracy: 0.7571\n",
            "Epoch 3258/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2592 - accuracy: 0.9000 - val_loss: 0.5303 - val_accuracy: 0.7571\n",
            "Epoch 3259/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2610 - accuracy: 0.8667 - val_loss: 0.5309 - val_accuracy: 0.7571\n",
            "Epoch 3260/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1511 - accuracy: 0.9667 - val_loss: 0.5310 - val_accuracy: 0.7571\n",
            "Epoch 3261/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1928 - accuracy: 0.9667 - val_loss: 0.5306 - val_accuracy: 0.7571\n",
            "Epoch 3262/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2527 - accuracy: 0.9333 - val_loss: 0.5283 - val_accuracy: 0.7714\n",
            "Epoch 3263/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1523 - accuracy: 0.9667 - val_loss: 0.5265 - val_accuracy: 0.7714\n",
            "Epoch 3264/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1623 - accuracy: 0.9000 - val_loss: 0.5250 - val_accuracy: 0.7714\n",
            "Epoch 3265/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2302 - accuracy: 0.9000 - val_loss: 0.5239 - val_accuracy: 0.7857\n",
            "Epoch 3266/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1496 - accuracy: 0.9667 - val_loss: 0.5227 - val_accuracy: 0.8000\n",
            "Epoch 3267/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1445 - accuracy: 0.9667 - val_loss: 0.5211 - val_accuracy: 0.8000\n",
            "Epoch 3268/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1751 - accuracy: 0.9000 - val_loss: 0.5201 - val_accuracy: 0.8000\n",
            "Epoch 3269/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1567 - accuracy: 0.9667 - val_loss: 0.5197 - val_accuracy: 0.8000\n",
            "Epoch 3270/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2714 - accuracy: 0.8667 - val_loss: 0.5184 - val_accuracy: 0.8000\n",
            "Epoch 3271/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1228 - accuracy: 1.0000 - val_loss: 0.5175 - val_accuracy: 0.8000\n",
            "Epoch 3272/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1321 - accuracy: 1.0000 - val_loss: 0.5168 - val_accuracy: 0.8000\n",
            "Epoch 3273/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1701 - accuracy: 0.9667 - val_loss: 0.5173 - val_accuracy: 0.8000\n",
            "Epoch 3274/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1900 - accuracy: 0.9333 - val_loss: 0.5175 - val_accuracy: 0.8000\n",
            "Epoch 3275/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2322 - accuracy: 0.9000 - val_loss: 0.5185 - val_accuracy: 0.8000\n",
            "Epoch 3276/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2460 - accuracy: 0.9000 - val_loss: 0.5180 - val_accuracy: 0.7857\n",
            "Epoch 3277/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1443 - accuracy: 0.9667 - val_loss: 0.5182 - val_accuracy: 0.7857\n",
            "Epoch 3278/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1900 - accuracy: 0.9333 - val_loss: 0.5186 - val_accuracy: 0.8000\n",
            "Epoch 3279/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1751 - accuracy: 0.9667 - val_loss: 0.5184 - val_accuracy: 0.8000\n",
            "Epoch 3280/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1831 - accuracy: 0.9333 - val_loss: 0.5182 - val_accuracy: 0.8000\n",
            "Epoch 3281/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2181 - accuracy: 0.9333 - val_loss: 0.5182 - val_accuracy: 0.8000\n",
            "Epoch 3282/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1528 - accuracy: 0.9667 - val_loss: 0.5189 - val_accuracy: 0.7714\n",
            "Epoch 3283/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1780 - accuracy: 0.9333 - val_loss: 0.5195 - val_accuracy: 0.7714\n",
            "Epoch 3284/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2393 - accuracy: 0.9333 - val_loss: 0.5203 - val_accuracy: 0.7714\n",
            "Epoch 3285/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1170 - accuracy: 1.0000 - val_loss: 0.5201 - val_accuracy: 0.7714\n",
            "Epoch 3286/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1397 - accuracy: 0.9667 - val_loss: 0.5198 - val_accuracy: 0.7714\n",
            "Epoch 3287/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2072 - accuracy: 0.9333 - val_loss: 0.5205 - val_accuracy: 0.7714\n",
            "Epoch 3288/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1975 - accuracy: 0.9000 - val_loss: 0.5206 - val_accuracy: 0.7714\n",
            "Epoch 3289/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2362 - accuracy: 0.9000 - val_loss: 0.5207 - val_accuracy: 0.7857\n",
            "Epoch 3290/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1754 - accuracy: 0.9333 - val_loss: 0.5213 - val_accuracy: 0.7857\n",
            "Epoch 3291/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2619 - accuracy: 0.8667 - val_loss: 0.5198 - val_accuracy: 0.7857\n",
            "Epoch 3292/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1641 - accuracy: 0.9333 - val_loss: 0.5181 - val_accuracy: 0.7857\n",
            "Epoch 3293/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1986 - accuracy: 0.9333 - val_loss: 0.5169 - val_accuracy: 0.7857\n",
            "Epoch 3294/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1960 - accuracy: 0.9333 - val_loss: 0.5149 - val_accuracy: 0.7857\n",
            "Epoch 3295/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1899 - accuracy: 0.9667 - val_loss: 0.5142 - val_accuracy: 0.7857\n",
            "Epoch 3296/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1246 - accuracy: 0.9667 - val_loss: 0.5129 - val_accuracy: 0.7857\n",
            "Epoch 3297/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2141 - accuracy: 0.8667 - val_loss: 0.5123 - val_accuracy: 0.7857\n",
            "Epoch 3298/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1541 - accuracy: 0.9000 - val_loss: 0.5111 - val_accuracy: 0.7857\n",
            "Epoch 3299/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2160 - accuracy: 0.9333 - val_loss: 0.5104 - val_accuracy: 0.7857\n",
            "Epoch 3300/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1802 - accuracy: 0.9667 - val_loss: 0.5096 - val_accuracy: 0.8000\n",
            "Epoch 3301/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1623 - accuracy: 0.9333 - val_loss: 0.5088 - val_accuracy: 0.8000\n",
            "Epoch 3302/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1924 - accuracy: 0.9000 - val_loss: 0.5074 - val_accuracy: 0.8000\n",
            "Epoch 3303/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2258 - accuracy: 0.9333 - val_loss: 0.5058 - val_accuracy: 0.8000\n",
            "Epoch 3304/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2024 - accuracy: 0.9333 - val_loss: 0.5042 - val_accuracy: 0.8000\n",
            "Epoch 3305/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1936 - accuracy: 0.9333 - val_loss: 0.5024 - val_accuracy: 0.8000\n",
            "Epoch 3306/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2212 - accuracy: 0.9000 - val_loss: 0.5017 - val_accuracy: 0.8000\n",
            "Epoch 3307/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1801 - accuracy: 0.9667 - val_loss: 0.5001 - val_accuracy: 0.8000\n",
            "Epoch 3308/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2422 - accuracy: 0.8667 - val_loss: 0.5006 - val_accuracy: 0.8000\n",
            "Epoch 3309/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1878 - accuracy: 0.9000 - val_loss: 0.5019 - val_accuracy: 0.8000\n",
            "Epoch 3310/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2279 - accuracy: 0.8667 - val_loss: 0.5051 - val_accuracy: 0.8000\n",
            "Epoch 3311/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2862 - accuracy: 0.9000 - val_loss: 0.5085 - val_accuracy: 0.7857\n",
            "Epoch 3312/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2353 - accuracy: 0.9000 - val_loss: 0.5136 - val_accuracy: 0.7857\n",
            "Epoch 3313/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1429 - accuracy: 1.0000 - val_loss: 0.5174 - val_accuracy: 0.7857\n",
            "Epoch 3314/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2985 - accuracy: 0.8667 - val_loss: 0.5215 - val_accuracy: 0.7714\n",
            "Epoch 3315/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2292 - accuracy: 0.8667 - val_loss: 0.5245 - val_accuracy: 0.7714\n",
            "Epoch 3316/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1248 - accuracy: 0.9667 - val_loss: 0.5285 - val_accuracy: 0.7714\n",
            "Epoch 3317/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1249 - accuracy: 0.9667 - val_loss: 0.5325 - val_accuracy: 0.7714\n",
            "Epoch 3318/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1998 - accuracy: 0.9333 - val_loss: 0.5362 - val_accuracy: 0.7714\n",
            "Epoch 3319/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2000 - accuracy: 0.9333 - val_loss: 0.5382 - val_accuracy: 0.7714\n",
            "Epoch 3320/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2933 - accuracy: 0.8667 - val_loss: 0.5400 - val_accuracy: 0.7571\n",
            "Epoch 3321/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2013 - accuracy: 0.9333 - val_loss: 0.5402 - val_accuracy: 0.7571\n",
            "Epoch 3322/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1288 - accuracy: 0.9667 - val_loss: 0.5406 - val_accuracy: 0.7571\n",
            "Epoch 3323/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1309 - accuracy: 0.9667 - val_loss: 0.5408 - val_accuracy: 0.7571\n",
            "Epoch 3324/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1288 - accuracy: 1.0000 - val_loss: 0.5409 - val_accuracy: 0.7571\n",
            "Epoch 3325/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2115 - accuracy: 0.9667 - val_loss: 0.5412 - val_accuracy: 0.7571\n",
            "Epoch 3326/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2016 - accuracy: 0.9333 - val_loss: 0.5420 - val_accuracy: 0.7571\n",
            "Epoch 3327/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2284 - accuracy: 0.9667 - val_loss: 0.5388 - val_accuracy: 0.7571\n",
            "Epoch 3328/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2067 - accuracy: 0.9333 - val_loss: 0.5355 - val_accuracy: 0.7571\n",
            "Epoch 3329/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.1711 - accuracy: 0.9667 - val_loss: 0.5325 - val_accuracy: 0.7571\n",
            "Epoch 3330/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1131 - accuracy: 0.9667 - val_loss: 0.5294 - val_accuracy: 0.7571\n",
            "Epoch 3331/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1595 - accuracy: 0.9667 - val_loss: 0.5261 - val_accuracy: 0.7714\n",
            "Epoch 3332/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1761 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.7714\n",
            "Epoch 3333/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1783 - accuracy: 0.9667 - val_loss: 0.5201 - val_accuracy: 0.7714\n",
            "Epoch 3334/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2583 - accuracy: 0.9000 - val_loss: 0.5188 - val_accuracy: 0.7714\n",
            "Epoch 3335/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1788 - accuracy: 0.9333 - val_loss: 0.5184 - val_accuracy: 0.7714\n",
            "Epoch 3336/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1929 - accuracy: 0.9333 - val_loss: 0.5183 - val_accuracy: 0.7714\n",
            "Epoch 3337/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1208 - accuracy: 0.9667 - val_loss: 0.5183 - val_accuracy: 0.7857\n",
            "Epoch 3338/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1370 - accuracy: 0.9667 - val_loss: 0.5185 - val_accuracy: 0.7857\n",
            "Epoch 3339/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1005 - accuracy: 0.9667 - val_loss: 0.5190 - val_accuracy: 0.7857\n",
            "Epoch 3340/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1884 - accuracy: 0.9667 - val_loss: 0.5183 - val_accuracy: 0.7857\n",
            "Epoch 3341/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1401 - accuracy: 0.9667 - val_loss: 0.5177 - val_accuracy: 0.7857\n",
            "Epoch 3342/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.2057 - accuracy: 0.9333 - val_loss: 0.5170 - val_accuracy: 0.7857\n",
            "Epoch 3343/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2142 - accuracy: 0.9000 - val_loss: 0.5162 - val_accuracy: 0.8000\n",
            "Epoch 3344/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1785 - accuracy: 0.9667 - val_loss: 0.5140 - val_accuracy: 0.8000\n",
            "Epoch 3345/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1942 - accuracy: 0.9333 - val_loss: 0.5119 - val_accuracy: 0.8286\n",
            "Epoch 3346/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2373 - accuracy: 0.9000 - val_loss: 0.5093 - val_accuracy: 0.8286\n",
            "Epoch 3347/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2240 - accuracy: 0.9000 - val_loss: 0.5072 - val_accuracy: 0.8429\n",
            "Epoch 3348/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1788 - accuracy: 0.9333 - val_loss: 0.5048 - val_accuracy: 0.8429\n",
            "Epoch 3349/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2344 - accuracy: 0.9333 - val_loss: 0.5010 - val_accuracy: 0.8429\n",
            "Epoch 3350/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2121 - accuracy: 0.9333 - val_loss: 0.4977 - val_accuracy: 0.8286\n",
            "Epoch 3351/4000\n",
            "1/1 [==============================] - 0s 89ms/step - loss: 0.2393 - accuracy: 0.9000 - val_loss: 0.4946 - val_accuracy: 0.8286\n",
            "Epoch 3352/4000\n",
            "1/1 [==============================] - 0s 82ms/step - loss: 0.2284 - accuracy: 0.9333 - val_loss: 0.4916 - val_accuracy: 0.8286\n",
            "Epoch 3353/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1611 - accuracy: 0.9667 - val_loss: 0.4899 - val_accuracy: 0.8286\n",
            "Epoch 3354/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1468 - accuracy: 0.9667 - val_loss: 0.4889 - val_accuracy: 0.8143\n",
            "Epoch 3355/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1886 - accuracy: 0.8667 - val_loss: 0.4889 - val_accuracy: 0.8286\n",
            "Epoch 3356/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1941 - accuracy: 0.9667 - val_loss: 0.4899 - val_accuracy: 0.8143\n",
            "Epoch 3357/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2130 - accuracy: 0.9333 - val_loss: 0.4917 - val_accuracy: 0.8000\n",
            "Epoch 3358/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1718 - accuracy: 0.9667 - val_loss: 0.4941 - val_accuracy: 0.7857\n",
            "Epoch 3359/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2388 - accuracy: 0.9000 - val_loss: 0.4966 - val_accuracy: 0.8000\n",
            "Epoch 3360/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2050 - accuracy: 0.8667 - val_loss: 0.5001 - val_accuracy: 0.7857\n",
            "Epoch 3361/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2426 - accuracy: 0.9000 - val_loss: 0.5028 - val_accuracy: 0.7857\n",
            "Epoch 3362/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1669 - accuracy: 0.9333 - val_loss: 0.5049 - val_accuracy: 0.7857\n",
            "Epoch 3363/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2061 - accuracy: 0.9333 - val_loss: 0.5066 - val_accuracy: 0.7857\n",
            "Epoch 3364/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1519 - accuracy: 0.9667 - val_loss: 0.5081 - val_accuracy: 0.7857\n",
            "Epoch 3365/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2105 - accuracy: 0.9333 - val_loss: 0.5101 - val_accuracy: 0.7714\n",
            "Epoch 3366/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2322 - accuracy: 0.9000 - val_loss: 0.5123 - val_accuracy: 0.7714\n",
            "Epoch 3367/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2367 - accuracy: 0.9000 - val_loss: 0.5159 - val_accuracy: 0.7714\n",
            "Epoch 3368/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1746 - accuracy: 0.9333 - val_loss: 0.5211 - val_accuracy: 0.7571\n",
            "Epoch 3369/4000\n",
            "1/1 [==============================] - 0s 81ms/step - loss: 0.2233 - accuracy: 0.9000 - val_loss: 0.5240 - val_accuracy: 0.7571\n",
            "Epoch 3370/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1997 - accuracy: 0.9333 - val_loss: 0.5273 - val_accuracy: 0.7571\n",
            "Epoch 3371/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1664 - accuracy: 0.9333 - val_loss: 0.5307 - val_accuracy: 0.7571\n",
            "Epoch 3372/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2443 - accuracy: 0.9000 - val_loss: 0.5336 - val_accuracy: 0.7571\n",
            "Epoch 3373/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1413 - accuracy: 0.9667 - val_loss: 0.5371 - val_accuracy: 0.7571\n",
            "Epoch 3374/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2323 - accuracy: 0.8667 - val_loss: 0.5425 - val_accuracy: 0.7429\n",
            "Epoch 3375/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2030 - accuracy: 0.9000 - val_loss: 0.5453 - val_accuracy: 0.7429\n",
            "Epoch 3376/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1646 - accuracy: 0.9667 - val_loss: 0.5473 - val_accuracy: 0.7429\n",
            "Epoch 3377/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1849 - accuracy: 0.9333 - val_loss: 0.5471 - val_accuracy: 0.7429\n",
            "Epoch 3378/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1602 - accuracy: 1.0000 - val_loss: 0.5479 - val_accuracy: 0.7429\n",
            "Epoch 3379/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1888 - accuracy: 0.9333 - val_loss: 0.5489 - val_accuracy: 0.7571\n",
            "Epoch 3380/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1902 - accuracy: 0.9667 - val_loss: 0.5497 - val_accuracy: 0.7571\n",
            "Epoch 3381/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2607 - accuracy: 0.8667 - val_loss: 0.5506 - val_accuracy: 0.7571\n",
            "Epoch 3382/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2453 - accuracy: 0.9000 - val_loss: 0.5507 - val_accuracy: 0.7571\n",
            "Epoch 3383/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2650 - accuracy: 0.8667 - val_loss: 0.5472 - val_accuracy: 0.7571\n",
            "Epoch 3384/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1797 - accuracy: 0.9333 - val_loss: 0.5452 - val_accuracy: 0.7571\n",
            "Epoch 3385/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1729 - accuracy: 0.9667 - val_loss: 0.5442 - val_accuracy: 0.7571\n",
            "Epoch 3386/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1782 - accuracy: 0.9000 - val_loss: 0.5430 - val_accuracy: 0.7571\n",
            "Epoch 3387/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1367 - accuracy: 0.9667 - val_loss: 0.5420 - val_accuracy: 0.7571\n",
            "Epoch 3388/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2339 - accuracy: 0.9667 - val_loss: 0.5398 - val_accuracy: 0.7571\n",
            "Epoch 3389/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2615 - accuracy: 0.8667 - val_loss: 0.5366 - val_accuracy: 0.7714\n",
            "Epoch 3390/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1919 - accuracy: 0.9333 - val_loss: 0.5350 - val_accuracy: 0.7714\n",
            "Epoch 3391/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1874 - accuracy: 0.9333 - val_loss: 0.5335 - val_accuracy: 0.7714\n",
            "Epoch 3392/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1709 - accuracy: 0.9333 - val_loss: 0.5325 - val_accuracy: 0.7714\n",
            "Epoch 3393/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2460 - accuracy: 0.9000 - val_loss: 0.5298 - val_accuracy: 0.7714\n",
            "Epoch 3394/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2192 - accuracy: 0.9000 - val_loss: 0.5275 - val_accuracy: 0.7714\n",
            "Epoch 3395/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2236 - accuracy: 0.9000 - val_loss: 0.5270 - val_accuracy: 0.7714\n",
            "Epoch 3396/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1591 - accuracy: 0.9667 - val_loss: 0.5267 - val_accuracy: 0.7714\n",
            "Epoch 3397/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1432 - accuracy: 1.0000 - val_loss: 0.5271 - val_accuracy: 0.7714\n",
            "Epoch 3398/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.1873 - accuracy: 0.9333 - val_loss: 0.5286 - val_accuracy: 0.7714\n",
            "Epoch 3399/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1898 - accuracy: 0.9667 - val_loss: 0.5287 - val_accuracy: 0.7714\n",
            "Epoch 3400/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2114 - accuracy: 0.9333 - val_loss: 0.5291 - val_accuracy: 0.7714\n",
            "Epoch 3401/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1971 - accuracy: 0.9000 - val_loss: 0.5301 - val_accuracy: 0.7714\n",
            "Epoch 3402/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1263 - accuracy: 0.9667 - val_loss: 0.5315 - val_accuracy: 0.7714\n",
            "Epoch 3403/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2213 - accuracy: 0.9000 - val_loss: 0.5324 - val_accuracy: 0.7714\n",
            "Epoch 3404/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1542 - accuracy: 0.9667 - val_loss: 0.5325 - val_accuracy: 0.7714\n",
            "Epoch 3405/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1920 - accuracy: 0.9333 - val_loss: 0.5326 - val_accuracy: 0.7714\n",
            "Epoch 3406/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2423 - accuracy: 0.9000 - val_loss: 0.5326 - val_accuracy: 0.7714\n",
            "Epoch 3407/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2120 - accuracy: 0.9000 - val_loss: 0.5306 - val_accuracy: 0.7714\n",
            "Epoch 3408/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1760 - accuracy: 0.9667 - val_loss: 0.5295 - val_accuracy: 0.7714\n",
            "Epoch 3409/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2152 - accuracy: 0.9000 - val_loss: 0.5284 - val_accuracy: 0.7714\n",
            "Epoch 3410/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2286 - accuracy: 0.9000 - val_loss: 0.5285 - val_accuracy: 0.7714\n",
            "Epoch 3411/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1285 - accuracy: 0.9667 - val_loss: 0.5284 - val_accuracy: 0.7571\n",
            "Epoch 3412/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2052 - accuracy: 0.9333 - val_loss: 0.5272 - val_accuracy: 0.7571\n",
            "Epoch 3413/4000\n",
            "1/1 [==============================] - 0s 78ms/step - loss: 0.1768 - accuracy: 0.9333 - val_loss: 0.5242 - val_accuracy: 0.7714\n",
            "Epoch 3414/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1973 - accuracy: 0.9000 - val_loss: 0.5208 - val_accuracy: 0.7714\n",
            "Epoch 3415/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1975 - accuracy: 0.9333 - val_loss: 0.5170 - val_accuracy: 0.7714\n",
            "Epoch 3416/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2416 - accuracy: 0.8333 - val_loss: 0.5135 - val_accuracy: 0.7714\n",
            "Epoch 3417/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1867 - accuracy: 0.9000 - val_loss: 0.5093 - val_accuracy: 0.7857\n",
            "Epoch 3418/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1459 - accuracy: 0.9333 - val_loss: 0.5055 - val_accuracy: 0.7714\n",
            "Epoch 3419/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1714 - accuracy: 0.9000 - val_loss: 0.5026 - val_accuracy: 0.7857\n",
            "Epoch 3420/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.2386 - accuracy: 0.9000 - val_loss: 0.5015 - val_accuracy: 0.7857\n",
            "Epoch 3421/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1436 - accuracy: 1.0000 - val_loss: 0.5010 - val_accuracy: 0.7714\n",
            "Epoch 3422/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1517 - accuracy: 0.9000 - val_loss: 0.5007 - val_accuracy: 0.7714\n",
            "Epoch 3423/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1903 - accuracy: 0.9333 - val_loss: 0.5011 - val_accuracy: 0.7857\n",
            "Epoch 3424/4000\n",
            "1/1 [==============================] - 0s 147ms/step - loss: 0.2880 - accuracy: 0.8000 - val_loss: 0.4995 - val_accuracy: 0.8000\n",
            "Epoch 3425/4000\n",
            "1/1 [==============================] - 0s 291ms/step - loss: 0.1988 - accuracy: 0.9333 - val_loss: 0.4975 - val_accuracy: 0.8000\n",
            "Epoch 3426/4000\n",
            "1/1 [==============================] - 0s 264ms/step - loss: 0.2010 - accuracy: 0.9333 - val_loss: 0.4964 - val_accuracy: 0.8000\n",
            "Epoch 3427/4000\n",
            "1/1 [==============================] - 0s 276ms/step - loss: 0.1920 - accuracy: 0.9667 - val_loss: 0.4960 - val_accuracy: 0.8000\n",
            "Epoch 3428/4000\n",
            "1/1 [==============================] - 0s 173ms/step - loss: 0.2083 - accuracy: 0.9000 - val_loss: 0.4967 - val_accuracy: 0.8143\n",
            "Epoch 3429/4000\n",
            "1/1 [==============================] - 0s 115ms/step - loss: 0.2071 - accuracy: 0.9333 - val_loss: 0.4978 - val_accuracy: 0.8143\n",
            "Epoch 3430/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1389 - accuracy: 0.9667 - val_loss: 0.4996 - val_accuracy: 0.8143\n",
            "Epoch 3431/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1401 - accuracy: 0.9333 - val_loss: 0.5016 - val_accuracy: 0.8143\n",
            "Epoch 3432/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1825 - accuracy: 0.9667 - val_loss: 0.5041 - val_accuracy: 0.8143\n",
            "Epoch 3433/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1930 - accuracy: 0.9333 - val_loss: 0.5079 - val_accuracy: 0.8143\n",
            "Epoch 3434/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1396 - accuracy: 1.0000 - val_loss: 0.5120 - val_accuracy: 0.8143\n",
            "Epoch 3435/4000\n",
            "1/1 [==============================] - 0s 165ms/step - loss: 0.1386 - accuracy: 0.9333 - val_loss: 0.5165 - val_accuracy: 0.8143\n",
            "Epoch 3436/4000\n",
            "1/1 [==============================] - 0s 213ms/step - loss: 0.1467 - accuracy: 0.9667 - val_loss: 0.5213 - val_accuracy: 0.7857\n",
            "Epoch 3437/4000\n",
            "1/1 [==============================] - 0s 279ms/step - loss: 0.2056 - accuracy: 0.8667 - val_loss: 0.5256 - val_accuracy: 0.7857\n",
            "Epoch 3438/4000\n",
            "1/1 [==============================] - 0s 292ms/step - loss: 0.1935 - accuracy: 0.9333 - val_loss: 0.5279 - val_accuracy: 0.7857\n",
            "Epoch 3439/4000\n",
            "1/1 [==============================] - 0s 155ms/step - loss: 0.1653 - accuracy: 0.9333 - val_loss: 0.5304 - val_accuracy: 0.7857\n",
            "Epoch 3440/4000\n",
            "1/1 [==============================] - 0s 99ms/step - loss: 0.1370 - accuracy: 0.9667 - val_loss: 0.5329 - val_accuracy: 0.7714\n",
            "Epoch 3441/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2034 - accuracy: 0.9333 - val_loss: 0.5343 - val_accuracy: 0.7714\n",
            "Epoch 3442/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2463 - accuracy: 0.9000 - val_loss: 0.5360 - val_accuracy: 0.7714\n",
            "Epoch 3443/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1840 - accuracy: 0.9667 - val_loss: 0.5367 - val_accuracy: 0.7714\n",
            "Epoch 3444/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2083 - accuracy: 0.8667 - val_loss: 0.5356 - val_accuracy: 0.7714\n",
            "Epoch 3445/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1897 - accuracy: 0.9667 - val_loss: 0.5331 - val_accuracy: 0.7857\n",
            "Epoch 3446/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1581 - accuracy: 0.9333 - val_loss: 0.5301 - val_accuracy: 0.7857\n",
            "Epoch 3447/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2094 - accuracy: 0.9333 - val_loss: 0.5287 - val_accuracy: 0.7857\n",
            "Epoch 3448/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1693 - accuracy: 0.9667 - val_loss: 0.5272 - val_accuracy: 0.7857\n",
            "Epoch 3449/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1672 - accuracy: 0.9333 - val_loss: 0.5273 - val_accuracy: 0.7857\n",
            "Epoch 3450/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1426 - accuracy: 0.9667 - val_loss: 0.5275 - val_accuracy: 0.7857\n",
            "Epoch 3451/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1602 - accuracy: 0.9333 - val_loss: 0.5270 - val_accuracy: 0.8000\n",
            "Epoch 3452/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2569 - accuracy: 0.9333 - val_loss: 0.5268 - val_accuracy: 0.8000\n",
            "Epoch 3453/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1199 - accuracy: 0.9667 - val_loss: 0.5266 - val_accuracy: 0.7857\n",
            "Epoch 3454/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2106 - accuracy: 0.9333 - val_loss: 0.5247 - val_accuracy: 0.8000\n",
            "Epoch 3455/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1349 - accuracy: 0.9333 - val_loss: 0.5217 - val_accuracy: 0.8000\n",
            "Epoch 3456/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1623 - accuracy: 0.9667 - val_loss: 0.5196 - val_accuracy: 0.8000\n",
            "Epoch 3457/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.3545 - accuracy: 0.9000 - val_loss: 0.5177 - val_accuracy: 0.8000\n",
            "Epoch 3458/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1454 - accuracy: 0.9333 - val_loss: 0.5165 - val_accuracy: 0.8000\n",
            "Epoch 3459/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1584 - accuracy: 0.9000 - val_loss: 0.5155 - val_accuracy: 0.8000\n",
            "Epoch 3460/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1743 - accuracy: 0.9667 - val_loss: 0.5150 - val_accuracy: 0.7857\n",
            "Epoch 3461/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2359 - accuracy: 0.9333 - val_loss: 0.5156 - val_accuracy: 0.7857\n",
            "Epoch 3462/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1435 - accuracy: 1.0000 - val_loss: 0.5166 - val_accuracy: 0.7857\n",
            "Epoch 3463/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2009 - accuracy: 0.8667 - val_loss: 0.5182 - val_accuracy: 0.7857\n",
            "Epoch 3464/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1898 - accuracy: 0.9333 - val_loss: 0.5189 - val_accuracy: 0.7857\n",
            "Epoch 3465/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1869 - accuracy: 0.9000 - val_loss: 0.5202 - val_accuracy: 0.7857\n",
            "Epoch 3466/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1771 - accuracy: 0.9667 - val_loss: 0.5209 - val_accuracy: 0.7857\n",
            "Epoch 3467/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1520 - accuracy: 0.9667 - val_loss: 0.5224 - val_accuracy: 0.7857\n",
            "Epoch 3468/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1477 - accuracy: 0.9667 - val_loss: 0.5247 - val_accuracy: 0.7857\n",
            "Epoch 3469/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1460 - accuracy: 0.9333 - val_loss: 0.5272 - val_accuracy: 0.7857\n",
            "Epoch 3470/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1478 - accuracy: 0.9333 - val_loss: 0.5301 - val_accuracy: 0.7714\n",
            "Epoch 3471/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2274 - accuracy: 0.8333 - val_loss: 0.5316 - val_accuracy: 0.7714\n",
            "Epoch 3472/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2192 - accuracy: 0.9333 - val_loss: 0.5328 - val_accuracy: 0.7714\n",
            "Epoch 3473/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2820 - accuracy: 0.8333 - val_loss: 0.5323 - val_accuracy: 0.7714\n",
            "Epoch 3474/4000\n",
            "1/1 [==============================] - 0s 82ms/step - loss: 0.2025 - accuracy: 0.9333 - val_loss: 0.5305 - val_accuracy: 0.7714\n",
            "Epoch 3475/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1086 - accuracy: 0.9667 - val_loss: 0.5289 - val_accuracy: 0.7714\n",
            "Epoch 3476/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1850 - accuracy: 0.9667 - val_loss: 0.5273 - val_accuracy: 0.7714\n",
            "Epoch 3477/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1782 - accuracy: 0.9333 - val_loss: 0.5245 - val_accuracy: 0.7857\n",
            "Epoch 3478/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1673 - accuracy: 0.9667 - val_loss: 0.5203 - val_accuracy: 0.8000\n",
            "Epoch 3479/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1371 - accuracy: 1.0000 - val_loss: 0.5155 - val_accuracy: 0.8000\n",
            "Epoch 3480/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1522 - accuracy: 0.9333 - val_loss: 0.5114 - val_accuracy: 0.8000\n",
            "Epoch 3481/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1948 - accuracy: 0.9333 - val_loss: 0.5072 - val_accuracy: 0.8000\n",
            "Epoch 3482/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1633 - accuracy: 0.9667 - val_loss: 0.5044 - val_accuracy: 0.8143\n",
            "Epoch 3483/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1551 - accuracy: 0.9333 - val_loss: 0.5027 - val_accuracy: 0.8143\n",
            "Epoch 3484/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2085 - accuracy: 0.9667 - val_loss: 0.5016 - val_accuracy: 0.8143\n",
            "Epoch 3485/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1277 - accuracy: 0.9000 - val_loss: 0.5011 - val_accuracy: 0.8143\n",
            "Epoch 3486/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2206 - accuracy: 0.8667 - val_loss: 0.5016 - val_accuracy: 0.8143\n",
            "Epoch 3487/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1674 - accuracy: 0.9333 - val_loss: 0.5025 - val_accuracy: 0.8000\n",
            "Epoch 3488/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2254 - accuracy: 0.9333 - val_loss: 0.5043 - val_accuracy: 0.8000\n",
            "Epoch 3489/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2416 - accuracy: 0.8000 - val_loss: 0.5076 - val_accuracy: 0.8000\n",
            "Epoch 3490/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.1276 - accuracy: 0.9667 - val_loss: 0.5115 - val_accuracy: 0.8000\n",
            "Epoch 3491/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1847 - accuracy: 0.9667 - val_loss: 0.5163 - val_accuracy: 0.8000\n",
            "Epoch 3492/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1272 - accuracy: 0.9667 - val_loss: 0.5207 - val_accuracy: 0.8000\n",
            "Epoch 3493/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1804 - accuracy: 0.9000 - val_loss: 0.5251 - val_accuracy: 0.8000\n",
            "Epoch 3494/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1430 - accuracy: 1.0000 - val_loss: 0.5304 - val_accuracy: 0.8000\n",
            "Epoch 3495/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1376 - accuracy: 0.9667 - val_loss: 0.5348 - val_accuracy: 0.7857\n",
            "Epoch 3496/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1795 - accuracy: 0.9333 - val_loss: 0.5395 - val_accuracy: 0.7857\n",
            "Epoch 3497/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1801 - accuracy: 0.9000 - val_loss: 0.5440 - val_accuracy: 0.7714\n",
            "Epoch 3498/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1716 - accuracy: 0.9667 - val_loss: 0.5475 - val_accuracy: 0.7714\n",
            "Epoch 3499/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2771 - accuracy: 0.9000 - val_loss: 0.5476 - val_accuracy: 0.7714\n",
            "Epoch 3500/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1931 - accuracy: 0.9667 - val_loss: 0.5463 - val_accuracy: 0.7714\n",
            "Epoch 3501/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1659 - accuracy: 0.9333 - val_loss: 0.5437 - val_accuracy: 0.7857\n",
            "Epoch 3502/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1602 - accuracy: 0.9667 - val_loss: 0.5407 - val_accuracy: 0.7857\n",
            "Epoch 3503/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2106 - accuracy: 0.9000 - val_loss: 0.5373 - val_accuracy: 0.8000\n",
            "Epoch 3504/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1406 - accuracy: 0.9667 - val_loss: 0.5337 - val_accuracy: 0.7857\n",
            "Epoch 3505/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1896 - accuracy: 0.9333 - val_loss: 0.5298 - val_accuracy: 0.7857\n",
            "Epoch 3506/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1931 - accuracy: 0.9000 - val_loss: 0.5282 - val_accuracy: 0.7857\n",
            "Epoch 3507/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1807 - accuracy: 0.9333 - val_loss: 0.5262 - val_accuracy: 0.7857\n",
            "Epoch 3508/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1271 - accuracy: 0.9667 - val_loss: 0.5240 - val_accuracy: 0.7857\n",
            "Epoch 3509/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2413 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.7857\n",
            "Epoch 3510/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1695 - accuracy: 0.9667 - val_loss: 0.5220 - val_accuracy: 0.7857\n",
            "Epoch 3511/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1246 - accuracy: 1.0000 - val_loss: 0.5222 - val_accuracy: 0.7857\n",
            "Epoch 3512/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2159 - accuracy: 0.9333 - val_loss: 0.5211 - val_accuracy: 0.7857\n",
            "Epoch 3513/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2391 - accuracy: 0.9000 - val_loss: 0.5200 - val_accuracy: 0.7857\n",
            "Epoch 3514/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2248 - accuracy: 0.9000 - val_loss: 0.5193 - val_accuracy: 0.7857\n",
            "Epoch 3515/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2440 - accuracy: 0.8667 - val_loss: 0.5187 - val_accuracy: 0.8000\n",
            "Epoch 3516/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.2328 - accuracy: 0.9333 - val_loss: 0.5175 - val_accuracy: 0.8000\n",
            "Epoch 3517/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2511 - accuracy: 0.8667 - val_loss: 0.5176 - val_accuracy: 0.8000\n",
            "Epoch 3518/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1820 - accuracy: 0.9667 - val_loss: 0.5175 - val_accuracy: 0.8000\n",
            "Epoch 3519/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1825 - accuracy: 0.9333 - val_loss: 0.5177 - val_accuracy: 0.8000\n",
            "Epoch 3520/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1832 - accuracy: 0.9000 - val_loss: 0.5184 - val_accuracy: 0.8000\n",
            "Epoch 3521/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1349 - accuracy: 0.9667 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3522/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2036 - accuracy: 0.9333 - val_loss: 0.5194 - val_accuracy: 0.8000\n",
            "Epoch 3523/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1218 - accuracy: 0.9333 - val_loss: 0.5204 - val_accuracy: 0.8000\n",
            "Epoch 3524/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2166 - accuracy: 0.8667 - val_loss: 0.5202 - val_accuracy: 0.8000\n",
            "Epoch 3525/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1366 - accuracy: 0.9333 - val_loss: 0.5206 - val_accuracy: 0.8000\n",
            "Epoch 3526/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1682 - accuracy: 0.9000 - val_loss: 0.5210 - val_accuracy: 0.8000\n",
            "Epoch 3527/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2843 - accuracy: 0.8667 - val_loss: 0.5225 - val_accuracy: 0.8000\n",
            "Epoch 3528/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1719 - accuracy: 0.9000 - val_loss: 0.5241 - val_accuracy: 0.7857\n",
            "Epoch 3529/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1095 - accuracy: 1.0000 - val_loss: 0.5265 - val_accuracy: 0.7857\n",
            "Epoch 3530/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1984 - accuracy: 0.9333 - val_loss: 0.5291 - val_accuracy: 0.7857\n",
            "Epoch 3531/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1775 - accuracy: 0.9667 - val_loss: 0.5311 - val_accuracy: 0.7857\n",
            "Epoch 3532/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1930 - accuracy: 0.9333 - val_loss: 0.5332 - val_accuracy: 0.7714\n",
            "Epoch 3533/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2710 - accuracy: 0.9000 - val_loss: 0.5326 - val_accuracy: 0.7714\n",
            "Epoch 3534/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1722 - accuracy: 0.9333 - val_loss: 0.5329 - val_accuracy: 0.7714\n",
            "Epoch 3535/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1930 - accuracy: 0.9667 - val_loss: 0.5315 - val_accuracy: 0.7714\n",
            "Epoch 3536/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1201 - accuracy: 1.0000 - val_loss: 0.5310 - val_accuracy: 0.7714\n",
            "Epoch 3537/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2311 - accuracy: 0.9333 - val_loss: 0.5291 - val_accuracy: 0.7857\n",
            "Epoch 3538/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2174 - accuracy: 0.9333 - val_loss: 0.5280 - val_accuracy: 0.7714\n",
            "Epoch 3539/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1714 - accuracy: 0.9667 - val_loss: 0.5266 - val_accuracy: 0.7714\n",
            "Epoch 3540/4000\n",
            "1/1 [==============================] - 0s 92ms/step - loss: 0.1823 - accuracy: 0.9333 - val_loss: 0.5253 - val_accuracy: 0.7857\n",
            "Epoch 3541/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2019 - accuracy: 0.9333 - val_loss: 0.5225 - val_accuracy: 0.7857\n",
            "Epoch 3542/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2146 - accuracy: 0.9333 - val_loss: 0.5201 - val_accuracy: 0.7857\n",
            "Epoch 3543/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1474 - accuracy: 0.9667 - val_loss: 0.5175 - val_accuracy: 0.7857\n",
            "Epoch 3544/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1621 - accuracy: 0.9000 - val_loss: 0.5137 - val_accuracy: 0.7857\n",
            "Epoch 3545/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2081 - accuracy: 0.9333 - val_loss: 0.5112 - val_accuracy: 0.7857\n",
            "Epoch 3546/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1957 - accuracy: 0.9333 - val_loss: 0.5093 - val_accuracy: 0.7857\n",
            "Epoch 3547/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2053 - accuracy: 0.9000 - val_loss: 0.5090 - val_accuracy: 0.8000\n",
            "Epoch 3548/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1815 - accuracy: 0.9333 - val_loss: 0.5096 - val_accuracy: 0.8000\n",
            "Epoch 3549/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2066 - accuracy: 0.9333 - val_loss: 0.5102 - val_accuracy: 0.8000\n",
            "Epoch 3550/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1938 - accuracy: 0.9333 - val_loss: 0.5117 - val_accuracy: 0.8000\n",
            "Epoch 3551/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1816 - accuracy: 0.9333 - val_loss: 0.5136 - val_accuracy: 0.8000\n",
            "Epoch 3552/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1634 - accuracy: 0.9333 - val_loss: 0.5162 - val_accuracy: 0.8000\n",
            "Epoch 3553/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1962 - accuracy: 0.9333 - val_loss: 0.5188 - val_accuracy: 0.8000\n",
            "Epoch 3554/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1794 - accuracy: 0.9000 - val_loss: 0.5224 - val_accuracy: 0.8000\n",
            "Epoch 3555/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1779 - accuracy: 0.9333 - val_loss: 0.5255 - val_accuracy: 0.7857\n",
            "Epoch 3556/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2633 - accuracy: 0.9333 - val_loss: 0.5266 - val_accuracy: 0.7857\n",
            "Epoch 3557/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1460 - accuracy: 0.9667 - val_loss: 0.5274 - val_accuracy: 0.7857\n",
            "Epoch 3558/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1655 - accuracy: 0.9667 - val_loss: 0.5273 - val_accuracy: 0.7857\n",
            "Epoch 3559/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1912 - accuracy: 0.9333 - val_loss: 0.5277 - val_accuracy: 0.7857\n",
            "Epoch 3560/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2913 - accuracy: 0.9333 - val_loss: 0.5277 - val_accuracy: 0.7857\n",
            "Epoch 3561/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1954 - accuracy: 0.9333 - val_loss: 0.5278 - val_accuracy: 0.7857\n",
            "Epoch 3562/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1449 - accuracy: 0.9667 - val_loss: 0.5279 - val_accuracy: 0.7857\n",
            "Epoch 3563/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1758 - accuracy: 0.9667 - val_loss: 0.5289 - val_accuracy: 0.7714\n",
            "Epoch 3564/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1789 - accuracy: 0.9333 - val_loss: 0.5305 - val_accuracy: 0.7714\n",
            "Epoch 3565/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1473 - accuracy: 0.9667 - val_loss: 0.5322 - val_accuracy: 0.7714\n",
            "Epoch 3566/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1736 - accuracy: 0.9667 - val_loss: 0.5329 - val_accuracy: 0.7714\n",
            "Epoch 3567/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2244 - accuracy: 0.9333 - val_loss: 0.5313 - val_accuracy: 0.7714\n",
            "Epoch 3568/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1516 - accuracy: 0.9333 - val_loss: 0.5297 - val_accuracy: 0.7714\n",
            "Epoch 3569/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1626 - accuracy: 0.9333 - val_loss: 0.5288 - val_accuracy: 0.7714\n",
            "Epoch 3570/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1572 - accuracy: 0.9667 - val_loss: 0.5290 - val_accuracy: 0.7714\n",
            "Epoch 3571/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1112 - accuracy: 1.0000 - val_loss: 0.5300 - val_accuracy: 0.7714\n",
            "Epoch 3572/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1834 - accuracy: 0.9333 - val_loss: 0.5331 - val_accuracy: 0.7714\n",
            "Epoch 3573/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1603 - accuracy: 0.9333 - val_loss: 0.5362 - val_accuracy: 0.7714\n",
            "Epoch 3574/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.3163 - accuracy: 0.8333 - val_loss: 0.5379 - val_accuracy: 0.7714\n",
            "Epoch 3575/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1442 - accuracy: 0.9667 - val_loss: 0.5392 - val_accuracy: 0.7571\n",
            "Epoch 3576/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1944 - accuracy: 0.9667 - val_loss: 0.5392 - val_accuracy: 0.7571\n",
            "Epoch 3577/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.0995 - accuracy: 1.0000 - val_loss: 0.5393 - val_accuracy: 0.7571\n",
            "Epoch 3578/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1786 - accuracy: 0.9667 - val_loss: 0.5390 - val_accuracy: 0.7571\n",
            "Epoch 3579/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1354 - accuracy: 0.9667 - val_loss: 0.5390 - val_accuracy: 0.7571\n",
            "Epoch 3580/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1278 - accuracy: 1.0000 - val_loss: 0.5395 - val_accuracy: 0.7571\n",
            "Epoch 3581/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1553 - accuracy: 0.9667 - val_loss: 0.5389 - val_accuracy: 0.7571\n",
            "Epoch 3582/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2356 - accuracy: 0.8667 - val_loss: 0.5380 - val_accuracy: 0.7571\n",
            "Epoch 3583/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2615 - accuracy: 0.9000 - val_loss: 0.5356 - val_accuracy: 0.7571\n",
            "Epoch 3584/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1535 - accuracy: 0.9667 - val_loss: 0.5321 - val_accuracy: 0.7714\n",
            "Epoch 3585/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1016 - accuracy: 1.0000 - val_loss: 0.5290 - val_accuracy: 0.7857\n",
            "Epoch 3586/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1318 - accuracy: 0.9667 - val_loss: 0.5261 - val_accuracy: 0.7857\n",
            "Epoch 3587/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1386 - accuracy: 0.9667 - val_loss: 0.5240 - val_accuracy: 0.7857\n",
            "Epoch 3588/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2017 - accuracy: 0.9333 - val_loss: 0.5228 - val_accuracy: 0.8000\n",
            "Epoch 3589/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1661 - accuracy: 0.9000 - val_loss: 0.5233 - val_accuracy: 0.8000\n",
            "Epoch 3590/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2172 - accuracy: 0.9000 - val_loss: 0.5231 - val_accuracy: 0.7857\n",
            "Epoch 3591/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1913 - accuracy: 0.9333 - val_loss: 0.5222 - val_accuracy: 0.7857\n",
            "Epoch 3592/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2001 - accuracy: 0.9000 - val_loss: 0.5224 - val_accuracy: 0.7857\n",
            "Epoch 3593/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1732 - accuracy: 0.9000 - val_loss: 0.5226 - val_accuracy: 0.8000\n",
            "Epoch 3594/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2147 - accuracy: 0.9000 - val_loss: 0.5224 - val_accuracy: 0.8000\n",
            "Epoch 3595/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1849 - accuracy: 0.9667 - val_loss: 0.5227 - val_accuracy: 0.8000\n",
            "Epoch 3596/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1200 - accuracy: 0.9667 - val_loss: 0.5232 - val_accuracy: 0.8000\n",
            "Epoch 3597/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1442 - accuracy: 0.9667 - val_loss: 0.5241 - val_accuracy: 0.7857\n",
            "Epoch 3598/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2044 - accuracy: 0.9000 - val_loss: 0.5227 - val_accuracy: 0.8000\n",
            "Epoch 3599/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1758 - accuracy: 0.9667 - val_loss: 0.5208 - val_accuracy: 0.8000\n",
            "Epoch 3600/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2577 - accuracy: 0.9000 - val_loss: 0.5188 - val_accuracy: 0.8000\n",
            "Epoch 3601/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2000 - accuracy: 0.9333 - val_loss: 0.5181 - val_accuracy: 0.8000\n",
            "Epoch 3602/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1560 - accuracy: 0.9667 - val_loss: 0.5176 - val_accuracy: 0.8000\n",
            "Epoch 3603/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1880 - accuracy: 0.9333 - val_loss: 0.5173 - val_accuracy: 0.8000\n",
            "Epoch 3604/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1911 - accuracy: 0.9000 - val_loss: 0.5167 - val_accuracy: 0.8000\n",
            "Epoch 3605/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1436 - accuracy: 1.0000 - val_loss: 0.5171 - val_accuracy: 0.8000\n",
            "Epoch 3606/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2174 - accuracy: 0.9333 - val_loss: 0.5180 - val_accuracy: 0.8000\n",
            "Epoch 3607/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1336 - accuracy: 1.0000 - val_loss: 0.5192 - val_accuracy: 0.8000\n",
            "Epoch 3608/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1437 - accuracy: 0.9667 - val_loss: 0.5202 - val_accuracy: 0.8000\n",
            "Epoch 3609/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.0837 - accuracy: 1.0000 - val_loss: 0.5211 - val_accuracy: 0.8000\n",
            "Epoch 3610/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2112 - accuracy: 0.9000 - val_loss: 0.5225 - val_accuracy: 0.8000\n",
            "Epoch 3611/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.0995 - accuracy: 0.9667 - val_loss: 0.5242 - val_accuracy: 0.7857\n",
            "Epoch 3612/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2150 - accuracy: 0.9000 - val_loss: 0.5255 - val_accuracy: 0.7857\n",
            "Epoch 3613/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1414 - accuracy: 0.9667 - val_loss: 0.5252 - val_accuracy: 0.7857\n",
            "Epoch 3614/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1792 - accuracy: 0.9333 - val_loss: 0.5261 - val_accuracy: 0.7857\n",
            "Epoch 3615/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2421 - accuracy: 0.9333 - val_loss: 0.5257 - val_accuracy: 0.7857\n",
            "Epoch 3616/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1894 - accuracy: 0.9333 - val_loss: 0.5248 - val_accuracy: 0.8000\n",
            "Epoch 3617/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2291 - accuracy: 0.8667 - val_loss: 0.5222 - val_accuracy: 0.8000\n",
            "Epoch 3618/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2545 - accuracy: 0.9333 - val_loss: 0.5192 - val_accuracy: 0.8000\n",
            "Epoch 3619/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1522 - accuracy: 0.9667 - val_loss: 0.5172 - val_accuracy: 0.8000\n",
            "Epoch 3620/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1512 - accuracy: 0.9667 - val_loss: 0.5156 - val_accuracy: 0.8000\n",
            "Epoch 3621/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2091 - accuracy: 0.9000 - val_loss: 0.5143 - val_accuracy: 0.8000\n",
            "Epoch 3622/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1891 - accuracy: 0.9333 - val_loss: 0.5126 - val_accuracy: 0.8000\n",
            "Epoch 3623/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1380 - accuracy: 0.9667 - val_loss: 0.5112 - val_accuracy: 0.8000\n",
            "Epoch 3624/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2129 - accuracy: 0.9333 - val_loss: 0.5092 - val_accuracy: 0.8000\n",
            "Epoch 3625/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1951 - accuracy: 0.9667 - val_loss: 0.5080 - val_accuracy: 0.8000\n",
            "Epoch 3626/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1698 - accuracy: 0.9333 - val_loss: 0.5065 - val_accuracy: 0.8000\n",
            "Epoch 3627/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.3212 - accuracy: 0.8667 - val_loss: 0.5039 - val_accuracy: 0.7857\n",
            "Epoch 3628/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1858 - accuracy: 0.9333 - val_loss: 0.5017 - val_accuracy: 0.7857\n",
            "Epoch 3629/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1767 - accuracy: 0.9333 - val_loss: 0.5004 - val_accuracy: 0.7857\n",
            "Epoch 3630/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2006 - accuracy: 0.8667 - val_loss: 0.4994 - val_accuracy: 0.8000\n",
            "Epoch 3631/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1430 - accuracy: 1.0000 - val_loss: 0.4998 - val_accuracy: 0.8000\n",
            "Epoch 3632/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1359 - accuracy: 0.9333 - val_loss: 0.5001 - val_accuracy: 0.8000\n",
            "Epoch 3633/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2461 - accuracy: 0.9667 - val_loss: 0.5002 - val_accuracy: 0.8000\n",
            "Epoch 3634/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2415 - accuracy: 0.9333 - val_loss: 0.4999 - val_accuracy: 0.8000\n",
            "Epoch 3635/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1402 - accuracy: 0.9667 - val_loss: 0.5001 - val_accuracy: 0.8000\n",
            "Epoch 3636/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1769 - accuracy: 0.9667 - val_loss: 0.5005 - val_accuracy: 0.8000\n",
            "Epoch 3637/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.3092 - accuracy: 0.8000 - val_loss: 0.5014 - val_accuracy: 0.8000\n",
            "Epoch 3638/4000\n",
            "1/1 [==============================] - 0s 78ms/step - loss: 0.2779 - accuracy: 0.8667 - val_loss: 0.5028 - val_accuracy: 0.8000\n",
            "Epoch 3639/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1558 - accuracy: 0.9667 - val_loss: 0.5039 - val_accuracy: 0.8000\n",
            "Epoch 3640/4000\n",
            "1/1 [==============================] - 0s 88ms/step - loss: 0.2082 - accuracy: 0.9000 - val_loss: 0.5058 - val_accuracy: 0.8000\n",
            "Epoch 3641/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.2014 - accuracy: 0.8667 - val_loss: 0.5073 - val_accuracy: 0.7714\n",
            "Epoch 3642/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2152 - accuracy: 0.9000 - val_loss: 0.5092 - val_accuracy: 0.7571\n",
            "Epoch 3643/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2080 - accuracy: 0.9667 - val_loss: 0.5116 - val_accuracy: 0.7857\n",
            "Epoch 3644/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1693 - accuracy: 0.9667 - val_loss: 0.5145 - val_accuracy: 0.7857\n",
            "Epoch 3645/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2301 - accuracy: 0.9000 - val_loss: 0.5189 - val_accuracy: 0.7857\n",
            "Epoch 3646/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1660 - accuracy: 0.9333 - val_loss: 0.5222 - val_accuracy: 0.7857\n",
            "Epoch 3647/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1933 - accuracy: 0.9000 - val_loss: 0.5267 - val_accuracy: 0.7857\n",
            "Epoch 3648/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2060 - accuracy: 0.9333 - val_loss: 0.5302 - val_accuracy: 0.7857\n",
            "Epoch 3649/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1374 - accuracy: 0.9667 - val_loss: 0.5345 - val_accuracy: 0.7857\n",
            "Epoch 3650/4000\n",
            "1/1 [==============================] - 0s 78ms/step - loss: 0.1782 - accuracy: 0.9333 - val_loss: 0.5397 - val_accuracy: 0.7714\n",
            "Epoch 3651/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1973 - accuracy: 0.9000 - val_loss: 0.5447 - val_accuracy: 0.7714\n",
            "Epoch 3652/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1993 - accuracy: 0.9333 - val_loss: 0.5512 - val_accuracy: 0.7571\n",
            "Epoch 3653/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.2044 - accuracy: 0.9333 - val_loss: 0.5595 - val_accuracy: 0.7571\n",
            "Epoch 3654/4000\n",
            "1/1 [==============================] - 0s 97ms/step - loss: 0.2199 - accuracy: 0.9333 - val_loss: 0.5648 - val_accuracy: 0.7571\n",
            "Epoch 3655/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1652 - accuracy: 0.9333 - val_loss: 0.5681 - val_accuracy: 0.7571\n",
            "Epoch 3656/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1888 - accuracy: 0.9000 - val_loss: 0.5713 - val_accuracy: 0.7571\n",
            "Epoch 3657/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.2035 - accuracy: 0.9667 - val_loss: 0.5744 - val_accuracy: 0.7571\n",
            "Epoch 3658/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2091 - accuracy: 0.9000 - val_loss: 0.5759 - val_accuracy: 0.7571\n",
            "Epoch 3659/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2347 - accuracy: 0.9000 - val_loss: 0.5760 - val_accuracy: 0.7714\n",
            "Epoch 3660/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1314 - accuracy: 0.9667 - val_loss: 0.5754 - val_accuracy: 0.7714\n",
            "Epoch 3661/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2305 - accuracy: 0.9333 - val_loss: 0.5737 - val_accuracy: 0.7714\n",
            "Epoch 3662/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1446 - accuracy: 0.9667 - val_loss: 0.5714 - val_accuracy: 0.7714\n",
            "Epoch 3663/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1911 - accuracy: 0.9000 - val_loss: 0.5661 - val_accuracy: 0.7714\n",
            "Epoch 3664/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2066 - accuracy: 0.9333 - val_loss: 0.5587 - val_accuracy: 0.7714\n",
            "Epoch 3665/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1169 - accuracy: 0.9667 - val_loss: 0.5520 - val_accuracy: 0.7714\n",
            "Epoch 3666/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2109 - accuracy: 0.9000 - val_loss: 0.5450 - val_accuracy: 0.7714\n",
            "Epoch 3667/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1421 - accuracy: 0.9667 - val_loss: 0.5387 - val_accuracy: 0.7714\n",
            "Epoch 3668/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1675 - accuracy: 0.9000 - val_loss: 0.5338 - val_accuracy: 0.7714\n",
            "Epoch 3669/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1251 - accuracy: 0.9667 - val_loss: 0.5296 - val_accuracy: 0.7857\n",
            "Epoch 3670/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1662 - accuracy: 0.9333 - val_loss: 0.5262 - val_accuracy: 0.7857\n",
            "Epoch 3671/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1741 - accuracy: 0.9667 - val_loss: 0.5236 - val_accuracy: 0.8000\n",
            "Epoch 3672/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1553 - accuracy: 0.9000 - val_loss: 0.5212 - val_accuracy: 0.8000\n",
            "Epoch 3673/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2396 - accuracy: 0.9000 - val_loss: 0.5191 - val_accuracy: 0.8000\n",
            "Epoch 3674/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1606 - accuracy: 0.9333 - val_loss: 0.5180 - val_accuracy: 0.8000\n",
            "Epoch 3675/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1660 - accuracy: 0.9667 - val_loss: 0.5180 - val_accuracy: 0.8000\n",
            "Epoch 3676/4000\n",
            "1/1 [==============================] - 0s 76ms/step - loss: 0.2869 - accuracy: 0.9333 - val_loss: 0.5174 - val_accuracy: 0.8000\n",
            "Epoch 3677/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1624 - accuracy: 0.9667 - val_loss: 0.5178 - val_accuracy: 0.8000\n",
            "Epoch 3678/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1901 - accuracy: 0.9000 - val_loss: 0.5187 - val_accuracy: 0.8000\n",
            "Epoch 3679/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1345 - accuracy: 0.9333 - val_loss: 0.5188 - val_accuracy: 0.8000\n",
            "Epoch 3680/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1882 - accuracy: 0.9333 - val_loss: 0.5186 - val_accuracy: 0.8000\n",
            "Epoch 3681/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1750 - accuracy: 0.9333 - val_loss: 0.5183 - val_accuracy: 0.8000\n",
            "Epoch 3682/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1581 - accuracy: 0.9667 - val_loss: 0.5181 - val_accuracy: 0.8000\n",
            "Epoch 3683/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1565 - accuracy: 0.9333 - val_loss: 0.5183 - val_accuracy: 0.8000\n",
            "Epoch 3684/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1624 - accuracy: 0.9333 - val_loss: 0.5182 - val_accuracy: 0.8000\n",
            "Epoch 3685/4000\n",
            "1/1 [==============================] - 0s 98ms/step - loss: 0.1809 - accuracy: 0.9333 - val_loss: 0.5184 - val_accuracy: 0.8000\n",
            "Epoch 3686/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1345 - accuracy: 0.9667 - val_loss: 0.5190 - val_accuracy: 0.8000\n",
            "Epoch 3687/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1951 - accuracy: 0.9000 - val_loss: 0.5182 - val_accuracy: 0.8000\n",
            "Epoch 3688/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1648 - accuracy: 0.9667 - val_loss: 0.5171 - val_accuracy: 0.8000\n",
            "Epoch 3689/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1869 - accuracy: 0.9667 - val_loss: 0.5174 - val_accuracy: 0.8000\n",
            "Epoch 3690/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2085 - accuracy: 0.9000 - val_loss: 0.5200 - val_accuracy: 0.8000\n",
            "Epoch 3691/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2124 - accuracy: 0.8667 - val_loss: 0.5214 - val_accuracy: 0.8000\n",
            "Epoch 3692/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2080 - accuracy: 0.9333 - val_loss: 0.5228 - val_accuracy: 0.8000\n",
            "Epoch 3693/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1939 - accuracy: 0.9333 - val_loss: 0.5243 - val_accuracy: 0.7857\n",
            "Epoch 3694/4000\n",
            "1/1 [==============================] - 0s 77ms/step - loss: 0.1098 - accuracy: 1.0000 - val_loss: 0.5252 - val_accuracy: 0.7857\n",
            "Epoch 3695/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2231 - accuracy: 0.9667 - val_loss: 0.5256 - val_accuracy: 0.7857\n",
            "Epoch 3696/4000\n",
            "1/1 [==============================] - 0s 86ms/step - loss: 0.3220 - accuracy: 0.9000 - val_loss: 0.5257 - val_accuracy: 0.7857\n",
            "Epoch 3697/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1257 - accuracy: 0.9667 - val_loss: 0.5263 - val_accuracy: 0.7857\n",
            "Epoch 3698/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1416 - accuracy: 0.9667 - val_loss: 0.5276 - val_accuracy: 0.7857\n",
            "Epoch 3699/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1858 - accuracy: 0.9667 - val_loss: 0.5287 - val_accuracy: 0.7857\n",
            "Epoch 3700/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2112 - accuracy: 0.9333 - val_loss: 0.5278 - val_accuracy: 0.7857\n",
            "Epoch 3701/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1442 - accuracy: 0.9667 - val_loss: 0.5265 - val_accuracy: 0.7857\n",
            "Epoch 3702/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2082 - accuracy: 0.9333 - val_loss: 0.5248 - val_accuracy: 0.7857\n",
            "Epoch 3703/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1246 - accuracy: 1.0000 - val_loss: 0.5241 - val_accuracy: 0.7857\n",
            "Epoch 3704/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1254 - accuracy: 0.9667 - val_loss: 0.5230 - val_accuracy: 0.8000\n",
            "Epoch 3705/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2551 - accuracy: 0.9333 - val_loss: 0.5229 - val_accuracy: 0.8000\n",
            "Epoch 3706/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1064 - accuracy: 1.0000 - val_loss: 0.5238 - val_accuracy: 0.7857\n",
            "Epoch 3707/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1887 - accuracy: 0.9333 - val_loss: 0.5242 - val_accuracy: 0.7857\n",
            "Epoch 3708/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1368 - accuracy: 0.9667 - val_loss: 0.5249 - val_accuracy: 0.7857\n",
            "Epoch 3709/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1689 - accuracy: 0.9333 - val_loss: 0.5256 - val_accuracy: 0.7857\n",
            "Epoch 3710/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1367 - accuracy: 0.9667 - val_loss: 0.5252 - val_accuracy: 0.8000\n",
            "Epoch 3711/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2042 - accuracy: 0.8667 - val_loss: 0.5255 - val_accuracy: 0.8000\n",
            "Epoch 3712/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2110 - accuracy: 0.9667 - val_loss: 0.5251 - val_accuracy: 0.8000\n",
            "Epoch 3713/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1885 - accuracy: 0.9333 - val_loss: 0.5235 - val_accuracy: 0.8000\n",
            "Epoch 3714/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1481 - accuracy: 0.9667 - val_loss: 0.5219 - val_accuracy: 0.8000\n",
            "Epoch 3715/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1880 - accuracy: 0.9333 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3716/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1713 - accuracy: 0.9667 - val_loss: 0.5162 - val_accuracy: 0.8000\n",
            "Epoch 3717/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1117 - accuracy: 1.0000 - val_loss: 0.5140 - val_accuracy: 0.8000\n",
            "Epoch 3718/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1259 - accuracy: 0.9667 - val_loss: 0.5122 - val_accuracy: 0.8000\n",
            "Epoch 3719/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1472 - accuracy: 0.9667 - val_loss: 0.5115 - val_accuracy: 0.8000\n",
            "Epoch 3720/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2018 - accuracy: 0.9333 - val_loss: 0.5095 - val_accuracy: 0.8000\n",
            "Epoch 3721/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2544 - accuracy: 0.9000 - val_loss: 0.5083 - val_accuracy: 0.8000\n",
            "Epoch 3722/4000\n",
            "1/1 [==============================] - 0s 79ms/step - loss: 0.1826 - accuracy: 0.9667 - val_loss: 0.5064 - val_accuracy: 0.8000\n",
            "Epoch 3723/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2362 - accuracy: 0.9000 - val_loss: 0.5060 - val_accuracy: 0.8000\n",
            "Epoch 3724/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1880 - accuracy: 0.9333 - val_loss: 0.5070 - val_accuracy: 0.8000\n",
            "Epoch 3725/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1614 - accuracy: 0.9667 - val_loss: 0.5094 - val_accuracy: 0.8000\n",
            "Epoch 3726/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1763 - accuracy: 0.9667 - val_loss: 0.5123 - val_accuracy: 0.8000\n",
            "Epoch 3727/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1837 - accuracy: 0.9333 - val_loss: 0.5151 - val_accuracy: 0.8000\n",
            "Epoch 3728/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2063 - accuracy: 0.9333 - val_loss: 0.5190 - val_accuracy: 0.8000\n",
            "Epoch 3729/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1626 - accuracy: 0.9333 - val_loss: 0.5211 - val_accuracy: 0.8000\n",
            "Epoch 3730/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2346 - accuracy: 0.9333 - val_loss: 0.5242 - val_accuracy: 0.8000\n",
            "Epoch 3731/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1666 - accuracy: 0.9667 - val_loss: 0.5263 - val_accuracy: 0.8000\n",
            "Epoch 3732/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1602 - accuracy: 0.9667 - val_loss: 0.5285 - val_accuracy: 0.8000\n",
            "Epoch 3733/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2097 - accuracy: 0.9000 - val_loss: 0.5305 - val_accuracy: 0.8000\n",
            "Epoch 3734/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1900 - accuracy: 0.9667 - val_loss: 0.5306 - val_accuracy: 0.8000\n",
            "Epoch 3735/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1928 - accuracy: 0.9667 - val_loss: 0.5302 - val_accuracy: 0.8000\n",
            "Epoch 3736/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1370 - accuracy: 0.9667 - val_loss: 0.5293 - val_accuracy: 0.8000\n",
            "Epoch 3737/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1728 - accuracy: 0.9667 - val_loss: 0.5277 - val_accuracy: 0.8000\n",
            "Epoch 3738/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1986 - accuracy: 0.9333 - val_loss: 0.5253 - val_accuracy: 0.8000\n",
            "Epoch 3739/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1751 - accuracy: 0.9667 - val_loss: 0.5216 - val_accuracy: 0.8000\n",
            "Epoch 3740/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1923 - accuracy: 0.9667 - val_loss: 0.5188 - val_accuracy: 0.8000\n",
            "Epoch 3741/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1759 - accuracy: 0.9333 - val_loss: 0.5160 - val_accuracy: 0.8000\n",
            "Epoch 3742/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1459 - accuracy: 0.9667 - val_loss: 0.5132 - val_accuracy: 0.8286\n",
            "Epoch 3743/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.2325 - accuracy: 0.9333 - val_loss: 0.5111 - val_accuracy: 0.8429\n",
            "Epoch 3744/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1918 - accuracy: 0.9667 - val_loss: 0.5095 - val_accuracy: 0.8429\n",
            "Epoch 3745/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2204 - accuracy: 0.9000 - val_loss: 0.5072 - val_accuracy: 0.8429\n",
            "Epoch 3746/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1851 - accuracy: 0.9000 - val_loss: 0.5067 - val_accuracy: 0.8429\n",
            "Epoch 3747/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1742 - accuracy: 0.9333 - val_loss: 0.5070 - val_accuracy: 0.8429\n",
            "Epoch 3748/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1334 - accuracy: 0.9333 - val_loss: 0.5082 - val_accuracy: 0.8429\n",
            "Epoch 3749/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1599 - accuracy: 0.9333 - val_loss: 0.5099 - val_accuracy: 0.8429\n",
            "Epoch 3750/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2157 - accuracy: 0.9000 - val_loss: 0.5113 - val_accuracy: 0.8286\n",
            "Epoch 3751/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1870 - accuracy: 0.9333 - val_loss: 0.5125 - val_accuracy: 0.8000\n",
            "Epoch 3752/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1734 - accuracy: 0.9667 - val_loss: 0.5143 - val_accuracy: 0.8000\n",
            "Epoch 3753/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1922 - accuracy: 0.9333 - val_loss: 0.5156 - val_accuracy: 0.8000\n",
            "Epoch 3754/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.2303 - accuracy: 0.8333 - val_loss: 0.5193 - val_accuracy: 0.8000\n",
            "Epoch 3755/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1840 - accuracy: 0.9333 - val_loss: 0.5223 - val_accuracy: 0.8000\n",
            "Epoch 3756/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2305 - accuracy: 0.9333 - val_loss: 0.5236 - val_accuracy: 0.8000\n",
            "Epoch 3757/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.1411 - accuracy: 0.9333 - val_loss: 0.5251 - val_accuracy: 0.8000\n",
            "Epoch 3758/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1698 - accuracy: 0.9333 - val_loss: 0.5269 - val_accuracy: 0.7857\n",
            "Epoch 3759/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1443 - accuracy: 0.9667 - val_loss: 0.5281 - val_accuracy: 0.7857\n",
            "Epoch 3760/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1913 - accuracy: 0.9333 - val_loss: 0.5285 - val_accuracy: 0.7857\n",
            "Epoch 3761/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1270 - accuracy: 0.9667 - val_loss: 0.5290 - val_accuracy: 0.7857\n",
            "Epoch 3762/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1598 - accuracy: 0.9333 - val_loss: 0.5282 - val_accuracy: 0.7857\n",
            "Epoch 3763/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2017 - accuracy: 0.9333 - val_loss: 0.5272 - val_accuracy: 0.7857\n",
            "Epoch 3764/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.2232 - accuracy: 0.9333 - val_loss: 0.5256 - val_accuracy: 0.7857\n",
            "Epoch 3765/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2003 - accuracy: 0.9333 - val_loss: 0.5236 - val_accuracy: 0.7857\n",
            "Epoch 3766/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1542 - accuracy: 0.9333 - val_loss: 0.5222 - val_accuracy: 0.7857\n",
            "Epoch 3767/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1412 - accuracy: 0.9333 - val_loss: 0.5211 - val_accuracy: 0.8000\n",
            "Epoch 3768/4000\n",
            "1/1 [==============================] - 0s 73ms/step - loss: 0.1937 - accuracy: 0.9667 - val_loss: 0.5196 - val_accuracy: 0.8000\n",
            "Epoch 3769/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2456 - accuracy: 0.8667 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3770/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1800 - accuracy: 0.9667 - val_loss: 0.5200 - val_accuracy: 0.8000\n",
            "Epoch 3771/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1643 - accuracy: 0.9667 - val_loss: 0.5216 - val_accuracy: 0.8000\n",
            "Epoch 3772/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2181 - accuracy: 0.8667 - val_loss: 0.5224 - val_accuracy: 0.8000\n",
            "Epoch 3773/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2115 - accuracy: 0.9333 - val_loss: 0.5227 - val_accuracy: 0.8000\n",
            "Epoch 3774/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1613 - accuracy: 0.9000 - val_loss: 0.5236 - val_accuracy: 0.8000\n",
            "Epoch 3775/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1869 - accuracy: 0.9000 - val_loss: 0.5254 - val_accuracy: 0.8000\n",
            "Epoch 3776/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1665 - accuracy: 0.9000 - val_loss: 0.5259 - val_accuracy: 0.7857\n",
            "Epoch 3777/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2517 - accuracy: 0.8000 - val_loss: 0.5280 - val_accuracy: 0.7857\n",
            "Epoch 3778/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1573 - accuracy: 0.9000 - val_loss: 0.5305 - val_accuracy: 0.7857\n",
            "Epoch 3779/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2870 - accuracy: 0.9000 - val_loss: 0.5325 - val_accuracy: 0.7857\n",
            "Epoch 3780/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1598 - accuracy: 0.9667 - val_loss: 0.5362 - val_accuracy: 0.7857\n",
            "Epoch 3781/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1720 - accuracy: 0.9333 - val_loss: 0.5410 - val_accuracy: 0.7714\n",
            "Epoch 3782/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1647 - accuracy: 0.9667 - val_loss: 0.5453 - val_accuracy: 0.7714\n",
            "Epoch 3783/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1809 - accuracy: 0.9333 - val_loss: 0.5502 - val_accuracy: 0.7714\n",
            "Epoch 3784/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1190 - accuracy: 0.9667 - val_loss: 0.5548 - val_accuracy: 0.7714\n",
            "Epoch 3785/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1938 - accuracy: 0.9333 - val_loss: 0.5599 - val_accuracy: 0.7714\n",
            "Epoch 3786/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1626 - accuracy: 0.9333 - val_loss: 0.5624 - val_accuracy: 0.7714\n",
            "Epoch 3787/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1301 - accuracy: 0.9667 - val_loss: 0.5640 - val_accuracy: 0.7714\n",
            "Epoch 3788/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.2346 - accuracy: 0.9333 - val_loss: 0.5651 - val_accuracy: 0.7714\n",
            "Epoch 3789/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.2312 - accuracy: 0.9333 - val_loss: 0.5638 - val_accuracy: 0.7714\n",
            "Epoch 3790/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1253 - accuracy: 1.0000 - val_loss: 0.5619 - val_accuracy: 0.7714\n",
            "Epoch 3791/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2887 - accuracy: 0.9000 - val_loss: 0.5581 - val_accuracy: 0.7714\n",
            "Epoch 3792/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.3054 - accuracy: 0.8333 - val_loss: 0.5524 - val_accuracy: 0.7714\n",
            "Epoch 3793/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1125 - accuracy: 0.9667 - val_loss: 0.5476 - val_accuracy: 0.7714\n",
            "Epoch 3794/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2429 - accuracy: 0.9333 - val_loss: 0.5422 - val_accuracy: 0.7857\n",
            "Epoch 3795/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2286 - accuracy: 0.9000 - val_loss: 0.5370 - val_accuracy: 0.7857\n",
            "Epoch 3796/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1798 - accuracy: 0.9333 - val_loss: 0.5332 - val_accuracy: 0.7857\n",
            "Epoch 3797/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1231 - accuracy: 0.9667 - val_loss: 0.5298 - val_accuracy: 0.7857\n",
            "Epoch 3798/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1608 - accuracy: 0.9333 - val_loss: 0.5284 - val_accuracy: 0.7857\n",
            "Epoch 3799/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1699 - accuracy: 0.9000 - val_loss: 0.5260 - val_accuracy: 0.8000\n",
            "Epoch 3800/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1219 - accuracy: 0.9333 - val_loss: 0.5234 - val_accuracy: 0.8000\n",
            "Epoch 3801/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2190 - accuracy: 0.8667 - val_loss: 0.5210 - val_accuracy: 0.8000\n",
            "Epoch 3802/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2015 - accuracy: 0.8667 - val_loss: 0.5197 - val_accuracy: 0.8000\n",
            "Epoch 3803/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1476 - accuracy: 0.9000 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3804/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1021 - accuracy: 0.9667 - val_loss: 0.5192 - val_accuracy: 0.8000\n",
            "Epoch 3805/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2011 - accuracy: 0.9333 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3806/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1454 - accuracy: 1.0000 - val_loss: 0.5199 - val_accuracy: 0.7857\n",
            "Epoch 3807/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1443 - accuracy: 0.9333 - val_loss: 0.5214 - val_accuracy: 0.7857\n",
            "Epoch 3808/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1198 - accuracy: 0.9667 - val_loss: 0.5219 - val_accuracy: 0.7857\n",
            "Epoch 3809/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1805 - accuracy: 0.9000 - val_loss: 0.5218 - val_accuracy: 0.8000\n",
            "Epoch 3810/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1652 - accuracy: 0.9333 - val_loss: 0.5222 - val_accuracy: 0.8000\n",
            "Epoch 3811/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1869 - accuracy: 0.9333 - val_loss: 0.5220 - val_accuracy: 0.8000\n",
            "Epoch 3812/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1610 - accuracy: 0.9667 - val_loss: 0.5208 - val_accuracy: 0.8000\n",
            "Epoch 3813/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2426 - accuracy: 0.9333 - val_loss: 0.5189 - val_accuracy: 0.8000\n",
            "Epoch 3814/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1764 - accuracy: 0.9333 - val_loss: 0.5168 - val_accuracy: 0.7857\n",
            "Epoch 3815/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1446 - accuracy: 0.9667 - val_loss: 0.5149 - val_accuracy: 0.7857\n",
            "Epoch 3816/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1925 - accuracy: 0.9333 - val_loss: 0.5128 - val_accuracy: 0.8000\n",
            "Epoch 3817/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1203 - accuracy: 0.9667 - val_loss: 0.5113 - val_accuracy: 0.8000\n",
            "Epoch 3818/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2016 - accuracy: 0.9333 - val_loss: 0.5085 - val_accuracy: 0.8000\n",
            "Epoch 3819/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2144 - accuracy: 0.9667 - val_loss: 0.5067 - val_accuracy: 0.8143\n",
            "Epoch 3820/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1285 - accuracy: 0.9667 - val_loss: 0.5045 - val_accuracy: 0.8143\n",
            "Epoch 3821/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1082 - accuracy: 1.0000 - val_loss: 0.5031 - val_accuracy: 0.8286\n",
            "Epoch 3822/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1924 - accuracy: 0.9000 - val_loss: 0.5024 - val_accuracy: 0.8286\n",
            "Epoch 3823/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2281 - accuracy: 0.8667 - val_loss: 0.5032 - val_accuracy: 0.8429\n",
            "Epoch 3824/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2321 - accuracy: 0.9000 - val_loss: 0.5042 - val_accuracy: 0.8429\n",
            "Epoch 3825/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1434 - accuracy: 0.9667 - val_loss: 0.5057 - val_accuracy: 0.8429\n",
            "Epoch 3826/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1524 - accuracy: 0.9333 - val_loss: 0.5075 - val_accuracy: 0.8429\n",
            "Epoch 3827/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1917 - accuracy: 0.9667 - val_loss: 0.5098 - val_accuracy: 0.8429\n",
            "Epoch 3828/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1755 - accuracy: 0.9667 - val_loss: 0.5132 - val_accuracy: 0.8429\n",
            "Epoch 3829/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1410 - accuracy: 0.9333 - val_loss: 0.5174 - val_accuracy: 0.8286\n",
            "Epoch 3830/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1992 - accuracy: 0.9000 - val_loss: 0.5209 - val_accuracy: 0.8143\n",
            "Epoch 3831/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.2262 - accuracy: 0.9000 - val_loss: 0.5234 - val_accuracy: 0.8143\n",
            "Epoch 3832/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1979 - accuracy: 0.8667 - val_loss: 0.5273 - val_accuracy: 0.8143\n",
            "Epoch 3833/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1863 - accuracy: 0.9667 - val_loss: 0.5312 - val_accuracy: 0.8000\n",
            "Epoch 3834/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1266 - accuracy: 0.9333 - val_loss: 0.5358 - val_accuracy: 0.7857\n",
            "Epoch 3835/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1809 - accuracy: 0.9333 - val_loss: 0.5402 - val_accuracy: 0.7714\n",
            "Epoch 3836/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1778 - accuracy: 0.9667 - val_loss: 0.5438 - val_accuracy: 0.7714\n",
            "Epoch 3837/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1327 - accuracy: 0.9667 - val_loss: 0.5475 - val_accuracy: 0.7714\n",
            "Epoch 3838/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1822 - accuracy: 0.9667 - val_loss: 0.5495 - val_accuracy: 0.7714\n",
            "Epoch 3839/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1889 - accuracy: 0.9000 - val_loss: 0.5504 - val_accuracy: 0.7571\n",
            "Epoch 3840/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1813 - accuracy: 0.9000 - val_loss: 0.5501 - val_accuracy: 0.7571\n",
            "Epoch 3841/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1870 - accuracy: 0.9000 - val_loss: 0.5490 - val_accuracy: 0.7571\n",
            "Epoch 3842/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1881 - accuracy: 0.9333 - val_loss: 0.5462 - val_accuracy: 0.7571\n",
            "Epoch 3843/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1788 - accuracy: 0.9333 - val_loss: 0.5435 - val_accuracy: 0.7714\n",
            "Epoch 3844/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.2192 - accuracy: 0.9667 - val_loss: 0.5394 - val_accuracy: 0.7857\n",
            "Epoch 3845/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1687 - accuracy: 0.9333 - val_loss: 0.5360 - val_accuracy: 0.7857\n",
            "Epoch 3846/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1769 - accuracy: 0.9333 - val_loss: 0.5331 - val_accuracy: 0.7857\n",
            "Epoch 3847/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2062 - accuracy: 0.9000 - val_loss: 0.5300 - val_accuracy: 0.7857\n",
            "Epoch 3848/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1461 - accuracy: 0.9333 - val_loss: 0.5276 - val_accuracy: 0.8000\n",
            "Epoch 3849/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.2673 - accuracy: 0.8667 - val_loss: 0.5259 - val_accuracy: 0.8000\n",
            "Epoch 3850/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2587 - accuracy: 0.8333 - val_loss: 0.5257 - val_accuracy: 0.8000\n",
            "Epoch 3851/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1605 - accuracy: 0.9667 - val_loss: 0.5257 - val_accuracy: 0.8000\n",
            "Epoch 3852/4000\n",
            "1/1 [==============================] - 0s 72ms/step - loss: 0.1819 - accuracy: 0.9000 - val_loss: 0.5267 - val_accuracy: 0.7857\n",
            "Epoch 3853/4000\n",
            "1/1 [==============================] - 0s 67ms/step - loss: 0.1405 - accuracy: 0.9667 - val_loss: 0.5276 - val_accuracy: 0.7857\n",
            "Epoch 3854/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1798 - accuracy: 0.9000 - val_loss: 0.5284 - val_accuracy: 0.7857\n",
            "Epoch 3855/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.2295 - accuracy: 0.9333 - val_loss: 0.5304 - val_accuracy: 0.7857\n",
            "Epoch 3856/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1457 - accuracy: 0.9667 - val_loss: 0.5322 - val_accuracy: 0.7857\n",
            "Epoch 3857/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2650 - accuracy: 0.9000 - val_loss: 0.5347 - val_accuracy: 0.7857\n",
            "Epoch 3858/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1584 - accuracy: 0.9667 - val_loss: 0.5363 - val_accuracy: 0.7857\n",
            "Epoch 3859/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1814 - accuracy: 0.9000 - val_loss: 0.5375 - val_accuracy: 0.7857\n",
            "Epoch 3860/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1450 - accuracy: 0.9667 - val_loss: 0.5384 - val_accuracy: 0.7857\n",
            "Epoch 3861/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2179 - accuracy: 0.9000 - val_loss: 0.5410 - val_accuracy: 0.7857\n",
            "Epoch 3862/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1780 - accuracy: 0.9333 - val_loss: 0.5435 - val_accuracy: 0.7857\n",
            "Epoch 3863/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1488 - accuracy: 0.9000 - val_loss: 0.5462 - val_accuracy: 0.7857\n",
            "Epoch 3864/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.2709 - accuracy: 0.8667 - val_loss: 0.5478 - val_accuracy: 0.7857\n",
            "Epoch 3865/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1505 - accuracy: 0.9333 - val_loss: 0.5498 - val_accuracy: 0.7714\n",
            "Epoch 3866/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1805 - accuracy: 0.8667 - val_loss: 0.5521 - val_accuracy: 0.7714\n",
            "Epoch 3867/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.2053 - accuracy: 0.9000 - val_loss: 0.5523 - val_accuracy: 0.7714\n",
            "Epoch 3868/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2110 - accuracy: 0.8667 - val_loss: 0.5526 - val_accuracy: 0.7714\n",
            "Epoch 3869/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.2040 - accuracy: 0.9333 - val_loss: 0.5542 - val_accuracy: 0.7714\n",
            "Epoch 3870/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2199 - accuracy: 0.9000 - val_loss: 0.5568 - val_accuracy: 0.7714\n",
            "Epoch 3871/4000\n",
            "1/1 [==============================] - 0s 68ms/step - loss: 0.1818 - accuracy: 0.9000 - val_loss: 0.5586 - val_accuracy: 0.7714\n",
            "Epoch 3872/4000\n",
            "1/1 [==============================] - 0s 74ms/step - loss: 0.2126 - accuracy: 0.8667 - val_loss: 0.5612 - val_accuracy: 0.7571\n",
            "Epoch 3873/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1413 - accuracy: 0.9000 - val_loss: 0.5641 - val_accuracy: 0.7571\n",
            "Epoch 3874/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2261 - accuracy: 0.9667 - val_loss: 0.5650 - val_accuracy: 0.7571\n",
            "Epoch 3875/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2322 - accuracy: 0.9000 - val_loss: 0.5646 - val_accuracy: 0.7571\n",
            "Epoch 3876/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1640 - accuracy: 0.9333 - val_loss: 0.5626 - val_accuracy: 0.7571\n",
            "Epoch 3877/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1230 - accuracy: 0.9667 - val_loss: 0.5603 - val_accuracy: 0.7571\n",
            "Epoch 3878/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1658 - accuracy: 0.9333 - val_loss: 0.5583 - val_accuracy: 0.7571\n",
            "Epoch 3879/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1504 - accuracy: 0.9333 - val_loss: 0.5555 - val_accuracy: 0.7571\n",
            "Epoch 3880/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2544 - accuracy: 0.9000 - val_loss: 0.5509 - val_accuracy: 0.7571\n",
            "Epoch 3881/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1552 - accuracy: 0.9333 - val_loss: 0.5458 - val_accuracy: 0.7571\n",
            "Epoch 3882/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1441 - accuracy: 0.9667 - val_loss: 0.5412 - val_accuracy: 0.7714\n",
            "Epoch 3883/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1673 - accuracy: 0.9333 - val_loss: 0.5380 - val_accuracy: 0.7714\n",
            "Epoch 3884/4000\n",
            "1/1 [==============================] - 0s 70ms/step - loss: 0.1783 - accuracy: 0.9667 - val_loss: 0.5350 - val_accuracy: 0.7714\n",
            "Epoch 3885/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1657 - accuracy: 0.9000 - val_loss: 0.5321 - val_accuracy: 0.7714\n",
            "Epoch 3886/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1238 - accuracy: 0.9333 - val_loss: 0.5304 - val_accuracy: 0.7714\n",
            "Epoch 3887/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1998 - accuracy: 0.9000 - val_loss: 0.5305 - val_accuracy: 0.7714\n",
            "Epoch 3888/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1545 - accuracy: 0.9667 - val_loss: 0.5300 - val_accuracy: 0.7714\n",
            "Epoch 3889/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1734 - accuracy: 0.9333 - val_loss: 0.5295 - val_accuracy: 0.7714\n",
            "Epoch 3890/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1731 - accuracy: 0.9667 - val_loss: 0.5295 - val_accuracy: 0.7857\n",
            "Epoch 3891/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2103 - accuracy: 0.9333 - val_loss: 0.5289 - val_accuracy: 0.8000\n",
            "Epoch 3892/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2053 - accuracy: 0.9000 - val_loss: 0.5283 - val_accuracy: 0.8143\n",
            "Epoch 3893/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1549 - accuracy: 0.9667 - val_loss: 0.5278 - val_accuracy: 0.8143\n",
            "Epoch 3894/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2109 - accuracy: 0.8667 - val_loss: 0.5291 - val_accuracy: 0.8143\n",
            "Epoch 3895/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1962 - accuracy: 0.9333 - val_loss: 0.5318 - val_accuracy: 0.8143\n",
            "Epoch 3896/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2312 - accuracy: 0.9000 - val_loss: 0.5340 - val_accuracy: 0.8143\n",
            "Epoch 3897/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1806 - accuracy: 0.9333 - val_loss: 0.5366 - val_accuracy: 0.8143\n",
            "Epoch 3898/4000\n",
            "1/1 [==============================] - 0s 85ms/step - loss: 0.1426 - accuracy: 0.9333 - val_loss: 0.5391 - val_accuracy: 0.8000\n",
            "Epoch 3899/4000\n",
            "1/1 [==============================] - 0s 66ms/step - loss: 0.1347 - accuracy: 0.9333 - val_loss: 0.5409 - val_accuracy: 0.8000\n",
            "Epoch 3900/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.1360 - accuracy: 0.9667 - val_loss: 0.5424 - val_accuracy: 0.8000\n",
            "Epoch 3901/4000\n",
            "1/1 [==============================] - 0s 75ms/step - loss: 0.1689 - accuracy: 0.9333 - val_loss: 0.5434 - val_accuracy: 0.8000\n",
            "Epoch 3902/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1812 - accuracy: 0.9333 - val_loss: 0.5435 - val_accuracy: 0.8000\n",
            "Epoch 3903/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1905 - accuracy: 0.9000 - val_loss: 0.5421 - val_accuracy: 0.8000\n",
            "Epoch 3904/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1215 - accuracy: 1.0000 - val_loss: 0.5417 - val_accuracy: 0.8000\n",
            "Epoch 3905/4000\n",
            "1/1 [==============================] - 0s 80ms/step - loss: 0.1222 - accuracy: 0.9667 - val_loss: 0.5416 - val_accuracy: 0.8143\n",
            "Epoch 3906/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.2245 - accuracy: 0.8667 - val_loss: 0.5418 - val_accuracy: 0.8143\n",
            "Epoch 3907/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.2078 - accuracy: 0.9000 - val_loss: 0.5413 - val_accuracy: 0.8143\n",
            "Epoch 3908/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1787 - accuracy: 0.9000 - val_loss: 0.5401 - val_accuracy: 0.8143\n",
            "Epoch 3909/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1815 - accuracy: 0.9333 - val_loss: 0.5402 - val_accuracy: 0.8143\n",
            "Epoch 3910/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1769 - accuracy: 0.9333 - val_loss: 0.5401 - val_accuracy: 0.8143\n",
            "Epoch 3911/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2398 - accuracy: 0.8667 - val_loss: 0.5409 - val_accuracy: 0.8143\n",
            "Epoch 3912/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1443 - accuracy: 0.9667 - val_loss: 0.5430 - val_accuracy: 0.8143\n",
            "Epoch 3913/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1971 - accuracy: 0.9333 - val_loss: 0.5455 - val_accuracy: 0.8000\n",
            "Epoch 3914/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1876 - accuracy: 0.9333 - val_loss: 0.5472 - val_accuracy: 0.8000\n",
            "Epoch 3915/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1419 - accuracy: 1.0000 - val_loss: 0.5497 - val_accuracy: 0.7857\n",
            "Epoch 3916/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2156 - accuracy: 0.9000 - val_loss: 0.5497 - val_accuracy: 0.7857\n",
            "Epoch 3917/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2364 - accuracy: 0.9000 - val_loss: 0.5489 - val_accuracy: 0.7857\n",
            "Epoch 3918/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1792 - accuracy: 0.9333 - val_loss: 0.5471 - val_accuracy: 0.7857\n",
            "Epoch 3919/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.1469 - accuracy: 0.9667 - val_loss: 0.5454 - val_accuracy: 0.7857\n",
            "Epoch 3920/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.1828 - accuracy: 0.9333 - val_loss: 0.5437 - val_accuracy: 0.7857\n",
            "Epoch 3921/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1687 - accuracy: 0.9667 - val_loss: 0.5420 - val_accuracy: 0.7857\n",
            "Epoch 3922/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.1792 - accuracy: 0.9000 - val_loss: 0.5399 - val_accuracy: 0.7857\n",
            "Epoch 3923/4000\n",
            "1/1 [==============================] - 0s 48ms/step - loss: 0.1481 - accuracy: 0.9667 - val_loss: 0.5370 - val_accuracy: 0.7857\n",
            "Epoch 3924/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2213 - accuracy: 0.8667 - val_loss: 0.5344 - val_accuracy: 0.8000\n",
            "Epoch 3925/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.2058 - accuracy: 0.9333 - val_loss: 0.5309 - val_accuracy: 0.8000\n",
            "Epoch 3926/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1729 - accuracy: 0.9667 - val_loss: 0.5289 - val_accuracy: 0.8000\n",
            "Epoch 3927/4000\n",
            "1/1 [==============================] - 0s 53ms/step - loss: 0.2543 - accuracy: 0.8667 - val_loss: 0.5256 - val_accuracy: 0.8000\n",
            "Epoch 3928/4000\n",
            "1/1 [==============================] - 0s 50ms/step - loss: 0.1703 - accuracy: 0.9667 - val_loss: 0.5232 - val_accuracy: 0.7857\n",
            "Epoch 3929/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1405 - accuracy: 0.9333 - val_loss: 0.5211 - val_accuracy: 0.7857\n",
            "Epoch 3930/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2084 - accuracy: 0.9000 - val_loss: 0.5197 - val_accuracy: 0.7857\n",
            "Epoch 3931/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1979 - accuracy: 0.9333 - val_loss: 0.5198 - val_accuracy: 0.7857\n",
            "Epoch 3932/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1732 - accuracy: 0.9333 - val_loss: 0.5208 - val_accuracy: 0.7714\n",
            "Epoch 3933/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1899 - accuracy: 0.9333 - val_loss: 0.5219 - val_accuracy: 0.7714\n",
            "Epoch 3934/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1724 - accuracy: 0.9667 - val_loss: 0.5226 - val_accuracy: 0.7857\n",
            "Epoch 3935/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1489 - accuracy: 0.9000 - val_loss: 0.5237 - val_accuracy: 0.7857\n",
            "Epoch 3936/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1784 - accuracy: 0.9333 - val_loss: 0.5243 - val_accuracy: 0.7857\n",
            "Epoch 3937/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1440 - accuracy: 0.9667 - val_loss: 0.5251 - val_accuracy: 0.7857\n",
            "Epoch 3938/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1699 - accuracy: 0.9333 - val_loss: 0.5251 - val_accuracy: 0.7857\n",
            "Epoch 3939/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1332 - accuracy: 0.9667 - val_loss: 0.5243 - val_accuracy: 0.7857\n",
            "Epoch 3940/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1466 - accuracy: 0.9333 - val_loss: 0.5232 - val_accuracy: 0.7857\n",
            "Epoch 3941/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1725 - accuracy: 0.9333 - val_loss: 0.5215 - val_accuracy: 0.8143\n",
            "Epoch 3942/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1204 - accuracy: 1.0000 - val_loss: 0.5202 - val_accuracy: 0.8143\n",
            "Epoch 3943/4000\n",
            "1/1 [==============================] - 0s 45ms/step - loss: 0.2492 - accuracy: 0.8667 - val_loss: 0.5183 - val_accuracy: 0.8143\n",
            "Epoch 3944/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1667 - accuracy: 0.9000 - val_loss: 0.5163 - val_accuracy: 0.8143\n",
            "Epoch 3945/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1418 - accuracy: 0.9667 - val_loss: 0.5148 - val_accuracy: 0.8143\n",
            "Epoch 3946/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1861 - accuracy: 0.9667 - val_loss: 0.5132 - val_accuracy: 0.8286\n",
            "Epoch 3947/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1585 - accuracy: 0.9333 - val_loss: 0.5118 - val_accuracy: 0.8429\n",
            "Epoch 3948/4000\n",
            "1/1 [==============================] - 0s 71ms/step - loss: 0.1432 - accuracy: 1.0000 - val_loss: 0.5108 - val_accuracy: 0.8429\n",
            "Epoch 3949/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1319 - accuracy: 0.9667 - val_loss: 0.5104 - val_accuracy: 0.8429\n",
            "Epoch 3950/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1577 - accuracy: 0.9000 - val_loss: 0.5100 - val_accuracy: 0.8429\n",
            "Epoch 3951/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2463 - accuracy: 0.9333 - val_loss: 0.5110 - val_accuracy: 0.8429\n",
            "Epoch 3952/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2722 - accuracy: 0.9000 - val_loss: 0.5126 - val_accuracy: 0.8429\n",
            "Epoch 3953/4000\n",
            "1/1 [==============================] - 0s 60ms/step - loss: 0.1917 - accuracy: 0.9000 - val_loss: 0.5153 - val_accuracy: 0.8143\n",
            "Epoch 3954/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.1859 - accuracy: 0.9000 - val_loss: 0.5175 - val_accuracy: 0.8143\n",
            "Epoch 3955/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1250 - accuracy: 1.0000 - val_loss: 0.5204 - val_accuracy: 0.8143\n",
            "Epoch 3956/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.2123 - accuracy: 0.8667 - val_loss: 0.5242 - val_accuracy: 0.8143\n",
            "Epoch 3957/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1210 - accuracy: 1.0000 - val_loss: 0.5272 - val_accuracy: 0.8143\n",
            "Epoch 3958/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.2230 - accuracy: 0.9333 - val_loss: 0.5295 - val_accuracy: 0.8143\n",
            "Epoch 3959/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1501 - accuracy: 0.9667 - val_loss: 0.5314 - val_accuracy: 0.8000\n",
            "Epoch 3960/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2141 - accuracy: 0.9000 - val_loss: 0.5317 - val_accuracy: 0.8000\n",
            "Epoch 3961/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1851 - accuracy: 0.9000 - val_loss: 0.5319 - val_accuracy: 0.7857\n",
            "Epoch 3962/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.2101 - accuracy: 0.9000 - val_loss: 0.5336 - val_accuracy: 0.7714\n",
            "Epoch 3963/4000\n",
            "1/1 [==============================] - 0s 69ms/step - loss: 0.1771 - accuracy: 0.9333 - val_loss: 0.5347 - val_accuracy: 0.7714\n",
            "Epoch 3964/4000\n",
            "1/1 [==============================] - 0s 43ms/step - loss: 0.1960 - accuracy: 0.9000 - val_loss: 0.5343 - val_accuracy: 0.7714\n",
            "Epoch 3965/4000\n",
            "1/1 [==============================] - 0s 47ms/step - loss: 0.2597 - accuracy: 0.8667 - val_loss: 0.5325 - val_accuracy: 0.7857\n",
            "Epoch 3966/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.1333 - accuracy: 0.9333 - val_loss: 0.5306 - val_accuracy: 0.7857\n",
            "Epoch 3967/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1615 - accuracy: 0.9667 - val_loss: 0.5300 - val_accuracy: 0.7857\n",
            "Epoch 3968/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2352 - accuracy: 0.8333 - val_loss: 0.5302 - val_accuracy: 0.7857\n",
            "Epoch 3969/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.2109 - accuracy: 0.8667 - val_loss: 0.5309 - val_accuracy: 0.8000\n",
            "Epoch 3970/4000\n",
            "1/1 [==============================] - 0s 83ms/step - loss: 0.1453 - accuracy: 0.9667 - val_loss: 0.5307 - val_accuracy: 0.8000\n",
            "Epoch 3971/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1806 - accuracy: 0.9333 - val_loss: 0.5304 - val_accuracy: 0.8000\n",
            "Epoch 3972/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.2673 - accuracy: 0.8667 - val_loss: 0.5294 - val_accuracy: 0.8000\n",
            "Epoch 3973/4000\n",
            "1/1 [==============================] - 0s 44ms/step - loss: 0.1848 - accuracy: 0.9667 - val_loss: 0.5286 - val_accuracy: 0.8000\n",
            "Epoch 3974/4000\n",
            "1/1 [==============================] - 0s 57ms/step - loss: 0.2046 - accuracy: 0.9333 - val_loss: 0.5281 - val_accuracy: 0.8000\n",
            "Epoch 3975/4000\n",
            "1/1 [==============================] - 0s 59ms/step - loss: 0.2059 - accuracy: 0.8667 - val_loss: 0.5282 - val_accuracy: 0.8000\n",
            "Epoch 3976/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1695 - accuracy: 0.9000 - val_loss: 0.5286 - val_accuracy: 0.8143\n",
            "Epoch 3977/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1373 - accuracy: 0.9333 - val_loss: 0.5298 - val_accuracy: 0.8143\n",
            "Epoch 3978/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1793 - accuracy: 0.9333 - val_loss: 0.5313 - val_accuracy: 0.8143\n",
            "Epoch 3979/4000\n",
            "1/1 [==============================] - 0s 55ms/step - loss: 0.1866 - accuracy: 0.9667 - val_loss: 0.5331 - val_accuracy: 0.8143\n",
            "Epoch 3980/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1044 - accuracy: 0.9667 - val_loss: 0.5354 - val_accuracy: 0.8143\n",
            "Epoch 3981/4000\n",
            "1/1 [==============================] - 0s 41ms/step - loss: 0.1371 - accuracy: 1.0000 - val_loss: 0.5380 - val_accuracy: 0.8000\n",
            "Epoch 3982/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1626 - accuracy: 0.9667 - val_loss: 0.5400 - val_accuracy: 0.8000\n",
            "Epoch 3983/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1547 - accuracy: 0.9000 - val_loss: 0.5421 - val_accuracy: 0.8000\n",
            "Epoch 3984/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.2310 - accuracy: 0.9333 - val_loss: 0.5437 - val_accuracy: 0.8000\n",
            "Epoch 3985/4000\n",
            "1/1 [==============================] - 0s 40ms/step - loss: 0.1911 - accuracy: 0.9333 - val_loss: 0.5450 - val_accuracy: 0.8000\n",
            "Epoch 3986/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1522 - accuracy: 0.9667 - val_loss: 0.5448 - val_accuracy: 0.7857\n",
            "Epoch 3987/4000\n",
            "1/1 [==============================] - 0s 42ms/step - loss: 0.1470 - accuracy: 0.9667 - val_loss: 0.5457 - val_accuracy: 0.7857\n",
            "Epoch 3988/4000\n",
            "1/1 [==============================] - 0s 64ms/step - loss: 0.1245 - accuracy: 0.9667 - val_loss: 0.5460 - val_accuracy: 0.7857\n",
            "Epoch 3989/4000\n",
            "1/1 [==============================] - 0s 52ms/step - loss: 0.0906 - accuracy: 0.9667 - val_loss: 0.5459 - val_accuracy: 0.7857\n",
            "Epoch 3990/4000\n",
            "1/1 [==============================] - 0s 49ms/step - loss: 0.1646 - accuracy: 0.9667 - val_loss: 0.5462 - val_accuracy: 0.7857\n",
            "Epoch 3991/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.1503 - accuracy: 0.9667 - val_loss: 0.5486 - val_accuracy: 0.7857\n",
            "Epoch 3992/4000\n",
            "1/1 [==============================] - 0s 56ms/step - loss: 0.1922 - accuracy: 0.9000 - val_loss: 0.5504 - val_accuracy: 0.7857\n",
            "Epoch 3993/4000\n",
            "1/1 [==============================] - 0s 51ms/step - loss: 0.1854 - accuracy: 0.9333 - val_loss: 0.5538 - val_accuracy: 0.7857\n",
            "Epoch 3994/4000\n",
            "1/1 [==============================] - 0s 62ms/step - loss: 0.1838 - accuracy: 0.9667 - val_loss: 0.5582 - val_accuracy: 0.7714\n",
            "Epoch 3995/4000\n",
            "1/1 [==============================] - 0s 61ms/step - loss: 0.1805 - accuracy: 0.9667 - val_loss: 0.5628 - val_accuracy: 0.7714\n",
            "Epoch 3996/4000\n",
            "1/1 [==============================] - 0s 65ms/step - loss: 0.1710 - accuracy: 0.9333 - val_loss: 0.5647 - val_accuracy: 0.7571\n",
            "Epoch 3997/4000\n",
            "1/1 [==============================] - 0s 58ms/step - loss: 0.1980 - accuracy: 0.9333 - val_loss: 0.5646 - val_accuracy: 0.7714\n",
            "Epoch 3998/4000\n",
            "1/1 [==============================] - 0s 46ms/step - loss: 0.1603 - accuracy: 0.9333 - val_loss: 0.5629 - val_accuracy: 0.7714\n",
            "Epoch 3999/4000\n",
            "1/1 [==============================] - 0s 54ms/step - loss: 0.1695 - accuracy: 0.9667 - val_loss: 0.5613 - val_accuracy: 0.7714\n",
            "Epoch 4000/4000\n",
            "1/1 [==============================] - 0s 63ms/step - loss: 0.2303 - accuracy: 0.9667 - val_loss: 0.5601 - val_accuracy: 0.7714\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# evaluate the model\n",
        "_, train_acc = model.evaluate(trainX, trainy, verbose=0)\n",
        "_, test_acc = model.evaluate(testX, testy, verbose=0)\n",
        "print('Train: %.3f, Test: %.3f' % (train_acc, test_acc))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Glcgu-zT_VbO",
        "outputId": "fb0e1f59-4b13-49a8-f05e-d44d7bb29dd7"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Train: 0.967, Test: 0.771\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# plot history\n",
        "pyplot.plot(history.history['accuracy'], label='train')\n",
        "pyplot.plot(history.history['val_accuracy'], label='test')\n",
        "pyplot.legend()\n",
        "pyplot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "HQLwqtXp_YyN",
        "outputId": "3c00975d-5fb7-4524-da06-bec922ee8e54"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "t7X_e4ig_VfS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "uSbmoeyc_RWb"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}