M_accelerate_ALL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center>MobileNet - Pytorch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Step 1: Prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# MobileNet-Pytorch\n",
    "import argparse \n",
    "import torch\n",
    "import numpy as np\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from torch.optim.lr_scheduler import StepLR\n",
    "from torchvision import datasets, transforms\n",
    "from torch.autograd import Variable\n",
    "from torch.utils.data.sampler import SubsetRandomSampler\n",
    "from sklearn.metrics import accuracy_score\n",
    "#from mobilenets import mobilenet\n",
    "\n",
    "use_cuda = torch.cuda.is_available()\n",
    "use_cudause_cud  = torch.cuda.is_available()\n",
    "dtype = torch.cuda.FloatTensor if use_cuda else torch.FloatTensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n"
     ]
    }
   ],
   "source": [
    "# Train, Validate, Test. Heavily inspired by Kevinzakka https://github.com/kevinzakka/DenseNet/blob/master/data_loader.py\n",
    "\n",
    "normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n",
    "                                 std=[0.229, 0.224, 0.225])\n",
    "\n",
    "valid_size=0.1\n",
    "\n",
    "# define transforms\n",
    "valid_transform = transforms.Compose([\n",
    "        transforms.ToTensor(),\n",
    "        normalize\n",
    "])\n",
    "\n",
    "train_transform = transforms.Compose([\n",
    "    transforms.RandomCrop(32, padding=4),\n",
    "    transforms.RandomHorizontalFlip(),\n",
    "    transforms.ToTensor(),\n",
    "    normalize\n",
    "])\n",
    "\n",
    "\n",
    "# load the dataset\n",
    "train_dataset = datasets.CIFAR10(root=\"data\", train=True, \n",
    "            download=True, transform=train_transform)\n",
    "\n",
    "valid_dataset = datasets.CIFAR10(root=\"data\", train=True, \n",
    "            download=True, transform=valid_transform)\n",
    "\n",
    "num_train = len(train_dataset)\n",
    "indices = list(range(num_train))\n",
    "split = int(np.floor(valid_size * num_train)) #5w张图片的10%用来当做验证集\n",
    "\n",
    "\n",
    "np.random.seed(42)# 42\n",
    "np.random.shuffle(indices) # 随机乱序[0,1,...,49999]\n",
    "\n",
    "train_idx, valid_idx = indices[split:], indices[:split]\n",
    "\n",
    "\n",
    "train_sampler = SubsetRandomSampler(train_idx) # 这个很有意思\n",
    "valid_sampler = SubsetRandomSampler(valid_idx)\n",
    "\n",
    "###################################################################################\n",
    "# ------------------------- 使用不同的批次大小 ------------------------------------\n",
    "###################################################################################\n",
    "\n",
    "show_step=2  # 批次大，show_step就小点\n",
    "max_epoch=150  # 训练最大epoch数目\n",
    "\n",
    "train_loader = torch.utils.data.DataLoader(train_dataset, \n",
    "                batch_size=256, sampler=train_sampler)\n",
    "\n",
    "valid_loader = torch.utils.data.DataLoader(valid_dataset, \n",
    "                batch_size=256, sampler=valid_sampler)\n",
    "\n",
    "\n",
    "test_transform = transforms.Compose([\n",
    "    transforms.ToTensor(), normalize\n",
    "])\n",
    "\n",
    "test_dataset = datasets.CIFAR10(root=\"data\", \n",
    "                                train=False, \n",
    "                                download=True,transform=test_transform)\n",
    "\n",
    "test_loader = torch.utils.data.DataLoader(test_dataset, \n",
    "                                          batch_size=1, \n",
    "                                          shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 2: Model Config"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# 32  缩放5次到 1x1@1024 \n",
    "# From https://github.com/kuangliu/pytorch-cifar \n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "\n",
    "class Block(nn.Module):\n",
    "    '''Depthwise conv + Pointwise conv'''\n",
    "    def __init__(self, in_planes, out_planes, stride=1):\n",
    "        super(Block, self).__init__()\n",
    "        \n",
    "        # 分组卷积数=输入通道数\n",
    "        self.conv1 = nn.Conv2d(in_planes, in_planes, kernel_size=3, stride=stride, padding=1, groups=in_planes, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(in_planes)\n",
    "        \n",
    "        \n",
    "        #self.conv2 = nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1, padding=0, bias=False)\n",
    "        \n",
    "        one_conv_kernel_size = 3\n",
    "        self.conv1D= nn.Conv1d(1, out_planes, one_conv_kernel_size, stride=1,padding=1,groups=1,dilation=1,bias=False) # 在__init__初始化        \n",
    "        \n",
    "        self.bn2 = nn.BatchNorm2d(out_planes)\n",
    "\n",
    "    def forward(self, x):\n",
    "        \n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        \n",
    "        # -------------------------- Attention -----------------------\n",
    "        w = F.avg_pool2d(x,x.shape[-1])  #最好在初始化层定义好\n",
    "        #print(w.shape)\n",
    "        # [bs,in_Channel,1,1]\n",
    "        w = w.view(w.shape[0],1,w.shape[1])\n",
    "        # [bs,1,in_Channel]\n",
    "        # one_conv_filter = nn.Conv1d(1, out_channel, one_conv_kernel_size, stride=1,padding=1,groups=1,dilation=1) # 在__init__初始化\n",
    "        # [bs,out_channel,in_Channel]\n",
    "        w = self.conv1D(w)\n",
    "        w = 0.5*F.tanh(w) # [-0.5,+0.5]\n",
    "        # -------------- softmax ---------------------------\n",
    "        #print(w.shape)\n",
    "        w = w.view(w.shape[0],w.shape[1],w.shape[2],1,1)\n",
    "        #print(w.shape)\n",
    "        \n",
    "        # ------------------------- fusion --------------------------\n",
    "        out=out.view(out.shape[0],1,out.shape[1],out.shape[2],out.shape[3])\n",
    "        #print(\"x size:\",out.shape)\n",
    "        \n",
    "        out=out*w\n",
    "        #print(\"after fusion x size:\",out.shape)\n",
    "        out=out.sum(dim=2)\n",
    "        \n",
    "        out = F.relu(self.bn2(out))\n",
    "        \n",
    "        return out\n",
    "\n",
    "\n",
    "class MobileNet(nn.Module):\n",
    "    # (128,2) means conv planes=128, conv stride=2, by default conv stride=1\n",
    "    cfg = [64, (128,2), 128, (256,2), 256, (512,2), 512, 512, 512, 512, 512, (1024,2), 1024]\n",
    "\n",
    "    def __init__(self, num_classes=10):\n",
    "        super(MobileNet, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, stride=1, padding=1, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(32)\n",
    "        self.layers = self._make_layers(in_planes=32) # 自动化构建层\n",
    "        self.linear = nn.Linear(1024, num_classes)\n",
    "\n",
    "    def _make_layers(self, in_planes):\n",
    "        layers = []\n",
    "        for x in self.cfg:\n",
    "            out_planes = x if isinstance(x, int) else x[0]\n",
    "            stride = 1 if isinstance(x, int) else x[1]\n",
    "            layers.append(Block(in_planes, out_planes, stride))\n",
    "            in_planes = out_planes\n",
    "        return nn.Sequential(*layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        out = self.layers(out)\n",
    "        out = F.avg_pool2d(out, 2)\n",
    "        out = out.view(out.size(0), -1)\n",
    "        out = self.linear(out)\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 32  缩放5次到 1x1@1024 \n",
    "# From https://github.com/kuangliu/pytorch-cifar \n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "class Block_Attention_HALF(nn.Module):\n",
    "    '''Depthwise conv + Pointwise conv'''\n",
    "    def __init__(self, in_planes, out_planes, stride=1):\n",
    "        super(Block_Attention_HALF, self).__init__()\n",
    "        \n",
    "        # 分组卷积数=输入通道数\n",
    "        self.conv1 = nn.Conv2d(in_planes, in_planes, kernel_size=3, stride=stride, padding=1, groups=in_planes, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(in_planes)\n",
    "        \n",
    "        #------------------------ 一半 ------------------------------\n",
    "        self.conv2 = nn.Conv2d(in_planes, out_planes//2, kernel_size=1, stride=1, padding=0, bias=False)\n",
    "        \n",
    "        #------------------------ 另一半 ----------------------------\n",
    "        one_conv_kernel_size = 9 # [3,7,9]\n",
    "        self.conv1D= nn.Conv1d(1, out_planes//2, one_conv_kernel_size, stride=1,padding=4,groups=1,dilation=1,bias=False) # 在__init__初始化        \n",
    "        \n",
    "        #------------------------------------------------------------\n",
    "        self.bn2 = nn.BatchNorm2d(out_planes)\n",
    "\n",
    "    def forward(self, x):\n",
    "        \n",
    "        out = F.relu6(self.bn1(self.conv1(x)))\n",
    "        #out = self.bn1(self.conv1(x))\n",
    "        # -------------------------- Attention -----------------------\n",
    "        w = F.avg_pool2d(x,x.shape[-1])  #最好在初始化层定义好\n",
    "        #print(w.shape)\n",
    "        # [bs,in_Channel,1,1]\n",
    "        in_channel=w.shape[1]\n",
    "        #w = w.view(w.shape[0],1,w.shape[1])\n",
    "        # [bs,1,in_Channel]\n",
    "        # 对这批数据取平均 且保留第0维\n",
    "        \n",
    "        #w= w.mean(dim=0,keepdim=True)\n",
    "        \n",
    "        \n",
    "#         MAX=w.shape[0]\n",
    "#         NUM=torch.floor(MAX*torch.rand(1)).long()\n",
    "#         if NUM>=0 and NUM<MAX:\n",
    "#             w=w[NUM]\n",
    "#         else:\n",
    "#             w=w[0]\n",
    "        \n",
    "        w=w[0]\n",
    "        \n",
    "        w=w.view(1,1,in_channel)\n",
    "        # [bs=1,1,in_Channel]\n",
    "        # one_conv_filter = nn.Conv1d(1, out_channel, one_conv_kernel_size, stride=1,padding=1,groups=1,dilation=1) # 在__init__初始化\n",
    "        # [bs=1,out_channel//2,in_Channel]\n",
    "        w = self.conv1D(w)\n",
    "        # [bs=1,out_channel//2,in_Channel]\n",
    "        \n",
    "        #-------------------------------------\n",
    "        w = F.tanh(w) # [-0.5,+0.5]\n",
    "        #w=F.relu6(w) # 效果大大折扣\n",
    "        \n",
    "        # [bs=1,out_channel//2,in_Channel]\n",
    "        w=w.view(w.shape[1],w.shape[2],1,1)\n",
    "        # [out_channel//2,in_Channel,1,1]\n",
    "        \n",
    "        # -------------- softmax ---------------------------\n",
    "        #print(w.shape)\n",
    "        \n",
    "        # ------------------------- fusion --------------------------\n",
    "       \n",
    "        # conv 1x1\n",
    "        out_1=self.conv2(out)\n",
    "        out_2=F.conv2d(out,w,bias=None,stride=1,groups=1,dilation=1)\n",
    "        out=torch.cat([out_1,out_2],1)\n",
    "        \n",
    "        # ----------------------- 试一试不要用relu -------------------------------\n",
    "        #out = self.bn2(out)\n",
    "        out=F.relu6(self.bn2(out))\n",
    "\n",
    "            \n",
    "        return out\n",
    "\n",
    "class Block_Attention(nn.Module):\n",
    "    '''Depthwise conv + Pointwise conv'''\n",
    "    def __init__(self, in_planes, out_planes, stride=1):\n",
    "        super(Block_Attention, self).__init__()\n",
    "        \n",
    "        # 分组卷积数=输入通道数\n",
    "        self.conv1 = nn.Conv2d(in_planes, in_planes, kernel_size=3, stride=stride, padding=1, groups=in_planes, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(in_planes)\n",
    "        \n",
    "        \n",
    "        #self.conv2 = nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1, padding=0, bias=False)\n",
    "        \n",
    "        one_conv_kernel_size = 17 # [3,7,9]\n",
    "        self.conv1D= nn.Conv1d(1, out_planes, one_conv_kernel_size, stride=1,padding=8,groups=1,dilation=1,bias=False) # 在__init__初始化        \n",
    "        \n",
    "        \n",
    "        self.bn2 = nn.BatchNorm2d(out_planes)\n",
    "\n",
    "    def forward(self, x):\n",
    "        \n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        \n",
    "        # -------------------------- Attention -----------------------\n",
    "        w = F.avg_pool2d(x,x.shape[-1])  #最好在初始化层定义好\n",
    "        #print(w.shape)\n",
    "        # [bs,in_Channel,1,1]\n",
    "        in_channel=w.shape[1]\n",
    "        #w = w.view(w.shape[0],1,w.shape[1])\n",
    "        # [bs,1,in_Channel]\n",
    "        # 对这批数据取平均 且保留第0维\n",
    "        \n",
    "        #w= w.mean(dim=0,keepdim=True)\n",
    "        \n",
    "        \n",
    "#         MAX=w.shape[0]\n",
    "#         NUM=torch.floor(MAX*torch.rand(1)).long()\n",
    "#         if NUM>=0 and NUM<MAX:\n",
    "#             w=w[NUM]\n",
    "#         else:\n",
    "#             w=w[0]\n",
    "        \n",
    "        w=w[0]\n",
    "        \n",
    "        w=w.view(1,1,in_channel)\n",
    "        # [bs=1,1,in_Channel]\n",
    "        # one_conv_filter = nn.Conv1d(1, out_channel, one_conv_kernel_size, stride=1,padding=1,groups=1,dilation=1) # 在__init__初始化\n",
    "        # [bs=1,out_channel,in_Channel]\n",
    "        w = self.conv1D(w)\n",
    "        # [bs=1,out_channel,in_Channel]\n",
    "        w = 0.5*F.tanh(w) # [-0.5,+0.5]\n",
    "         # [bs=1,out_channel,in_Channel]\n",
    "        w=w.view(w.shape[1],w.shape[2],1,1)\n",
    "        # [out_channel,in_Channel,1,1]\n",
    "        \n",
    "        # -------------- softmax ---------------------------\n",
    "        #print(w.shape)\n",
    "        \n",
    "        # ------------------------- fusion --------------------------\n",
    "       \n",
    "        # conv 1x1\n",
    "        out=F.conv2d(out,w,bias=None,stride=1,groups=1,dilation=1)\n",
    "\n",
    "        out = F.relu(self.bn2(out))\n",
    "        \n",
    "        return out\n",
    "\n",
    "\n",
    "class Block(nn.Module):\n",
    "    '''Depthwise conv + Pointwise conv'''\n",
    "    def __init__(self, in_planes, out_planes, stride=1):\n",
    "        super(Block, self).__init__()\n",
    "        \n",
    "        # 分组卷积数=输入通道数\n",
    "        self.conv1 = nn.Conv2d(in_planes, in_planes, kernel_size=3, stride=stride, padding=1, groups=in_planes, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(in_planes)\n",
    "        \n",
    "        self.conv2 = nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1, padding=0, bias=False)\n",
    "        \n",
    "        self.bn2 = nn.BatchNorm2d(out_planes)\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        out = F.relu(self.bn2(self.conv2(out)))\n",
    "        return out\n",
    "\n",
    "\n",
    "class MobileNet(nn.Module):\n",
    "    # (128,2) means conv planes=128, conv stride=2, by default conv stride=1\n",
    "    #cfg = [64, (128,2), 128, (256,2), 256, (512,2), 512, 512, 512, 512, 512, (1024,2), 1024]\n",
    "    \n",
    "    #cfg = [64, (128,2), 128, (256,2), 256, (512,2), 512, 512, 512, 512, 512, (1024,2), [1024,1]]\n",
    "    cfg = [64, (128,2), 128, (256,2), (256,1), (512,2), [512,1], [512,1], [512,1],[512,1], [512,1], [1024,2], [1024,1]]\n",
    "    \n",
    "    def __init__(self, num_classes=10):\n",
    "        super(MobileNet, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, stride=1, padding=1, bias=False)\n",
    "        \n",
    "        self.bn1 = nn.BatchNorm2d(32)\n",
    "        self.layers = self._make_layers(in_planes=32) # 自动化构建层\n",
    "        self.linear = nn.Linear(1024, num_classes)\n",
    "\n",
    "    def _make_layers(self, in_planes):\n",
    "        layers = []\n",
    "        for x in self.cfg:\n",
    "            if isinstance(x, int):\n",
    "                out_planes = x\n",
    "                stride = 1 \n",
    "                layers.append(Block(in_planes, out_planes, stride))\n",
    "            elif isinstance(x, tuple):\n",
    "                out_planes = x[0]\n",
    "                stride = x[1]\n",
    "                layers.append(Block(in_planes, out_planes, stride))\n",
    "            # AC层通过list存放设置参数\n",
    "            elif isinstance(x, list):\n",
    "                out_planes= x[0]\n",
    "                stride = x[1] if len(x)==2 else 1\n",
    "                layers.append(Block_Attention_HALF(in_planes, out_planes, stride))   \n",
    "            else:\n",
    "                pass\n",
    "            \n",
    "            in_planes = out_planes\n",
    "            \n",
    "        return nn.Sequential(*layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        out = self.layers(out)\n",
    "        out = F.avg_pool2d(out, 2)\n",
    "        out = out.view(out.size(0), -1)\n",
    "        out = self.linear(out)\n",
    "        return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# From https://github.com/Z0m6ie/CIFAR-10_PyTorch\n",
    "#model = mobilenet(num_classes=10, large_img=False)\n",
    "\n",
    "# From https://github.com/kuangliu/pytorch-cifar \n",
    "if torch.cuda.is_available():\n",
    "    model=MobileNet(10).cuda()\n",
    "else:\n",
    "    model=MobileNet(10)\n",
    "\n",
    "optimizer = optim.Adam(model.parameters(), lr=0.01)\n",
    "scheduler = StepLR(optimizer, step_size=20, gamma=0.5)\n",
    "criterion = nn.CrossEntropyLoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Implement validation\n",
    "def train(epoch):\n",
    "    model.train()\n",
    "    #writer = SummaryWriter()\n",
    "    for batch_idx, (data, target) in enumerate(train_loader):\n",
    "        if use_cuda:\n",
    "            data, target = data.cuda(), target.cuda()\n",
    "        data, target = Variable(data), Variable(target)\n",
    "        optimizer.zero_grad()\n",
    "        output = model(data)\n",
    "        correct = 0\n",
    "        pred = output.data.max(1, keepdim=True)[1] # get the index of the max log-probability\n",
    "        correct += pred.eq(target.data.view_as(pred)).sum()\n",
    "        \n",
    "        loss = criterion(output, target)\n",
    "        loss.backward()\n",
    "        accuracy = 100. * (correct.cpu().numpy()/ len(output))\n",
    "        optimizer.step()\n",
    "        if batch_idx % 5*show_step == 0:\n",
    "#             if batch_idx % 2*show_step == 0:\n",
    "#                 print(model.layers[1].conv1D.weight.shape)\n",
    "#                 print(model.layers[1].conv1D.weight[0:2][0:2])\n",
    "            \n",
    "            print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}, Accuracy: {:.2f}'.format(\n",
    "                epoch, batch_idx * len(data), len(train_loader.dataset),\n",
    "                100. * batch_idx / len(train_loader), loss.item(), accuracy))\n",
    "            f1=open(\"Cifar10_INFO.txt\",\"a+\")\n",
    "            f1.write(\"\\n\"+'Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}, Accuracy: {:.2f}'.format(\n",
    "                epoch, batch_idx * len(data), len(train_loader.dataset),\n",
    "                100. * batch_idx / len(train_loader), loss.item(), accuracy))\n",
    "            f1.close()\n",
    "            \n",
    "            #writer.add_scalar('Loss/Loss', loss.item(), epoch)\n",
    "            #writer.add_scalar('Accuracy/Accuracy', accuracy, epoch)\n",
    "    scheduler.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def validate(epoch):\n",
    "    model.eval()\n",
    "    #writer = SummaryWriter()\n",
    "    valid_loss = 0\n",
    "    correct = 0\n",
    "    for data, target in valid_loader:\n",
    "        if use_cuda:\n",
    "            data, target = data.cuda(), target.cuda()\n",
    "        data, target = Variable(data), Variable(target)\n",
    "        output = model(data)\n",
    "        valid_loss += F.cross_entropy(output, target, size_average=False).item() # sum up batch loss\n",
    "        pred = output.data.max(1, keepdim=True)[1] # get the index of the max log-probability\n",
    "        correct += pred.eq(target.data.view_as(pred)).sum()\n",
    "\n",
    "    valid_loss /= len(valid_idx)\n",
    "    accuracy = 100. * correct.cpu().numpy() / len(valid_idx)\n",
    "    print('\\nValidation set: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n'.format(\n",
    "        valid_loss, correct, len(valid_idx),\n",
    "        100. * correct / len(valid_idx)))\n",
    "    \n",
    "    f1=open(\"Cifar10_INFO.txt\",\"a+\")\n",
    "    f1.write('\\nValidation set: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n'.format(\n",
    "        valid_loss, correct, len(valid_idx),\n",
    "        100. * correct / len(valid_idx)))\n",
    "    f1.close()\n",
    "    #writer.add_scalar('Loss/Validation_Loss', valid_loss, epoch)\n",
    "    #writer.add_scalar('Accuracy/Validation_Accuracy', accuracy, epoch)\n",
    "    return valid_loss, accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Fix best model\n",
    "\n",
    "def test(epoch):\n",
    "    model.eval()\n",
    "    test_loss = 0\n",
    "    correct = 0\n",
    "    for data, target in test_loader:\n",
    "        if use_cuda:\n",
    "            data, target = data.cuda(), target.cuda()\n",
    "        data, target = Variable(data), Variable(target)\n",
    "        output = model(data)\n",
    "        test_loss += F.cross_entropy(output, target, size_average=False).item() # sum up batch loss\n",
    "        pred = output.data.max(1, keepdim=True)[1] # get the index of the max log-probability\n",
    "        correct += pred.eq(target.data.view_as(pred)).cpu().sum()\n",
    "\n",
    "    test_loss /= len(test_loader.dataset)\n",
    "    print('\\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n'.format(\n",
    "        test_loss, correct, len(test_loader.dataset),\n",
    "        100. * correct.cpu().numpy() / len(test_loader.dataset)))\n",
    "    \n",
    "    f1=open(\"Cifar10_INFO.txt\",\"a+\")\n",
    "    f1.write('\\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.2f}%)\\n'.format(\n",
    "        test_loss, correct, len(test_loader.dataset),\n",
    "        100. * correct.cpu().numpy() / len(test_loader.dataset)))\n",
    "    f1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def save_best(loss, accuracy, best_loss, best_acc):\n",
    "    if best_loss == None:\n",
    "        best_loss = loss\n",
    "        best_acc = accuracy\n",
    "        file = 'saved_models/best_save_model.p'\n",
    "        torch.save(model.state_dict(), file)\n",
    "        \n",
    "    elif loss < best_loss and accuracy > best_acc:\n",
    "        best_loss = loss\n",
    "        best_acc = accuracy\n",
    "        file = 'saved_models/best_save_model.p'\n",
    "        torch.save(model.state_dict(), file)\n",
    "    return best_loss, best_acc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 0 [0/50000 (0%)]\tLoss: 2.317187, Accuracy: 10.16\n",
      "Train Epoch: 0 [1280/50000 (3%)]\tLoss: 2.739555, Accuracy: 9.38\n",
      "Train Epoch: 0 [2560/50000 (6%)]\tLoss: 2.468929, Accuracy: 9.77\n",
      "Train Epoch: 0 [3840/50000 (9%)]\tLoss: 2.271804, Accuracy: 11.72\n",
      "Train Epoch: 0 [5120/50000 (11%)]\tLoss: 2.214532, Accuracy: 16.80\n",
      "Train Epoch: 0 [6400/50000 (14%)]\tLoss: 2.125456, Accuracy: 18.36\n",
      "Train Epoch: 0 [7680/50000 (17%)]\tLoss: 2.063283, Accuracy: 18.75\n",
      "Train Epoch: 0 [8960/50000 (20%)]\tLoss: 1.957888, Accuracy: 25.39\n",
      "Train Epoch: 0 [10240/50000 (23%)]\tLoss: 2.006796, Accuracy: 23.05\n",
      "Train Epoch: 0 [11520/50000 (26%)]\tLoss: 1.940412, Accuracy: 26.56\n",
      "Train Epoch: 0 [12800/50000 (28%)]\tLoss: 1.925677, Accuracy: 23.83\n",
      "Train Epoch: 0 [14080/50000 (31%)]\tLoss: 1.894595, Accuracy: 26.95\n",
      "Train Epoch: 0 [15360/50000 (34%)]\tLoss: 1.874364, Accuracy: 28.12\n",
      "Train Epoch: 0 [16640/50000 (37%)]\tLoss: 1.920679, Accuracy: 23.83\n",
      "Train Epoch: 0 [17920/50000 (40%)]\tLoss: 1.921081, Accuracy: 26.95\n",
      "Train Epoch: 0 [19200/50000 (43%)]\tLoss: 1.870906, Accuracy: 23.05\n",
      "Train Epoch: 0 [20480/50000 (45%)]\tLoss: 1.905605, Accuracy: 28.52\n",
      "Train Epoch: 0 [21760/50000 (48%)]\tLoss: 1.875262, Accuracy: 25.78\n",
      "Train Epoch: 0 [23040/50000 (51%)]\tLoss: 1.760782, Accuracy: 31.25\n",
      "Train Epoch: 0 [24320/50000 (54%)]\tLoss: 1.815875, Accuracy: 29.69\n",
      "Train Epoch: 0 [25600/50000 (57%)]\tLoss: 1.789346, Accuracy: 28.12\n",
      "Train Epoch: 0 [26880/50000 (60%)]\tLoss: 1.729920, Accuracy: 32.81\n",
      "Train Epoch: 0 [28160/50000 (62%)]\tLoss: 1.692929, Accuracy: 39.06\n",
      "Train Epoch: 0 [29440/50000 (65%)]\tLoss: 1.751308, Accuracy: 35.94\n",
      "Train Epoch: 0 [30720/50000 (68%)]\tLoss: 1.733815, Accuracy: 29.30\n",
      "Train Epoch: 0 [32000/50000 (71%)]\tLoss: 1.748714, Accuracy: 37.50\n",
      "Train Epoch: 0 [33280/50000 (74%)]\tLoss: 1.753810, Accuracy: 28.52\n",
      "Train Epoch: 0 [34560/50000 (77%)]\tLoss: 1.652142, Accuracy: 37.50\n",
      "Train Epoch: 0 [35840/50000 (80%)]\tLoss: 1.726063, Accuracy: 28.91\n",
      "Train Epoch: 0 [37120/50000 (82%)]\tLoss: 1.670838, Accuracy: 34.38\n",
      "Train Epoch: 0 [38400/50000 (85%)]\tLoss: 1.573907, Accuracy: 43.36\n",
      "Train Epoch: 0 [39680/50000 (88%)]\tLoss: 1.650179, Accuracy: 35.16\n",
      "Train Epoch: 0 [40960/50000 (91%)]\tLoss: 1.646149, Accuracy: 37.89\n",
      "Train Epoch: 0 [42240/50000 (94%)]\tLoss: 1.821646, Accuracy: 35.16\n",
      "Train Epoch: 0 [43520/50000 (97%)]\tLoss: 1.581002, Accuracy: 39.06\n",
      "Train Epoch: 0 [35000/50000 (99%)]\tLoss: 1.636860, Accuracy: 37.00\n",
      "\n",
      "Validation set: Average loss: 4.5531, Accuracy: 1197/5000 (23.00%)\n",
      "\n",
      "the time of this epoch:[21.662639617919922 s]\n",
      "Train Epoch: 1 [0/50000 (0%)]\tLoss: 1.654787, Accuracy: 39.06\n",
      "Train Epoch: 1 [1280/50000 (3%)]\tLoss: 1.533673, Accuracy: 39.45\n",
      "Train Epoch: 1 [2560/50000 (6%)]\tLoss: 1.631841, Accuracy: 32.42\n",
      "Train Epoch: 1 [3840/50000 (9%)]\tLoss: 1.631126, Accuracy: 38.67\n",
      "Train Epoch: 1 [5120/50000 (11%)]\tLoss: 1.639353, Accuracy: 38.67\n",
      "Train Epoch: 1 [6400/50000 (14%)]\tLoss: 1.574432, Accuracy: 44.53\n",
      "Train Epoch: 1 [7680/50000 (17%)]\tLoss: 1.517393, Accuracy: 47.27\n",
      "Train Epoch: 1 [8960/50000 (20%)]\tLoss: 1.620072, Accuracy: 39.84\n",
      "Train Epoch: 1 [10240/50000 (23%)]\tLoss: 1.485670, Accuracy: 45.31\n",
      "Train Epoch: 1 [11520/50000 (26%)]\tLoss: 1.407409, Accuracy: 48.44\n",
      "Train Epoch: 1 [12800/50000 (28%)]\tLoss: 1.564423, Accuracy: 42.19\n",
      "Train Epoch: 1 [14080/50000 (31%)]\tLoss: 1.428197, Accuracy: 44.14\n",
      "Train Epoch: 1 [15360/50000 (34%)]\tLoss: 1.486374, Accuracy: 44.53\n",
      "Train Epoch: 1 [16640/50000 (37%)]\tLoss: 1.496168, Accuracy: 46.09\n",
      "Train Epoch: 1 [17920/50000 (40%)]\tLoss: 1.353985, Accuracy: 48.05\n",
      "Train Epoch: 1 [19200/50000 (43%)]\tLoss: 1.440946, Accuracy: 49.61\n",
      "Train Epoch: 1 [20480/50000 (45%)]\tLoss: 1.428810, Accuracy: 49.61\n",
      "Train Epoch: 1 [21760/50000 (48%)]\tLoss: 1.366629, Accuracy: 51.56\n",
      "Train Epoch: 1 [23040/50000 (51%)]\tLoss: 1.520613, Accuracy: 41.41\n",
      "Train Epoch: 1 [24320/50000 (54%)]\tLoss: 1.424382, Accuracy: 45.70\n",
      "Train Epoch: 1 [25600/50000 (57%)]\tLoss: 1.417356, Accuracy: 49.61\n",
      "Train Epoch: 1 [26880/50000 (60%)]\tLoss: 1.472661, Accuracy: 45.31\n",
      "Train Epoch: 1 [28160/50000 (62%)]\tLoss: 1.338052, Accuracy: 47.66\n",
      "Train Epoch: 1 [29440/50000 (65%)]\tLoss: 1.241622, Accuracy: 57.42\n",
      "Train Epoch: 1 [30720/50000 (68%)]\tLoss: 1.254776, Accuracy: 51.56\n",
      "Train Epoch: 1 [32000/50000 (71%)]\tLoss: 1.353367, Accuracy: 50.00\n",
      "Train Epoch: 1 [33280/50000 (74%)]\tLoss: 1.335058, Accuracy: 50.00\n",
      "Train Epoch: 1 [34560/50000 (77%)]\tLoss: 1.464982, Accuracy: 48.83\n",
      "Train Epoch: 1 [35840/50000 (80%)]\tLoss: 1.362602, Accuracy: 54.30\n",
      "Train Epoch: 1 [37120/50000 (82%)]\tLoss: 1.333230, Accuracy: 52.73\n",
      "Train Epoch: 1 [38400/50000 (85%)]\tLoss: 1.346182, Accuracy: 49.22\n",
      "Train Epoch: 1 [39680/50000 (88%)]\tLoss: 1.174814, Accuracy: 58.98\n",
      "Train Epoch: 1 [40960/50000 (91%)]\tLoss: 1.270859, Accuracy: 51.17\n",
      "Train Epoch: 1 [42240/50000 (94%)]\tLoss: 1.222242, Accuracy: 59.38\n",
      "Train Epoch: 1 [43520/50000 (97%)]\tLoss: 1.269724, Accuracy: 54.30\n",
      "Train Epoch: 1 [35000/50000 (99%)]\tLoss: 1.163435, Accuracy: 57.00\n",
      "\n",
      "Validation set: Average loss: 4.8672, Accuracy: 1912/5000 (38.00%)\n",
      "\n",
      "the time of this epoch:[21.558705806732178 s]\n",
      "Train Epoch: 2 [0/50000 (0%)]\tLoss: 1.170546, Accuracy: 58.20\n",
      "Train Epoch: 2 [1280/50000 (3%)]\tLoss: 1.167825, Accuracy: 55.86\n",
      "Train Epoch: 2 [2560/50000 (6%)]\tLoss: 1.267082, Accuracy: 57.03\n",
      "Train Epoch: 2 [3840/50000 (9%)]\tLoss: 1.203408, Accuracy: 57.42\n",
      "Train Epoch: 2 [5120/50000 (11%)]\tLoss: 1.226529, Accuracy: 49.22\n",
      "Train Epoch: 2 [6400/50000 (14%)]\tLoss: 1.311463, Accuracy: 53.91\n",
      "Train Epoch: 2 [7680/50000 (17%)]\tLoss: 1.213612, Accuracy: 59.38\n",
      "Train Epoch: 2 [8960/50000 (20%)]\tLoss: 1.147260, Accuracy: 56.64\n",
      "Train Epoch: 2 [10240/50000 (23%)]\tLoss: 1.254088, Accuracy: 55.08\n",
      "Train Epoch: 2 [11520/50000 (26%)]\tLoss: 1.197541, Accuracy: 56.25\n",
      "Train Epoch: 2 [12800/50000 (28%)]\tLoss: 1.137027, Accuracy: 55.86\n",
      "Train Epoch: 2 [14080/50000 (31%)]\tLoss: 1.194584, Accuracy: 61.33\n",
      "Train Epoch: 2 [15360/50000 (34%)]\tLoss: 1.204290, Accuracy: 60.16\n",
      "Train Epoch: 2 [16640/50000 (37%)]\tLoss: 1.172325, Accuracy: 55.86\n",
      "Train Epoch: 2 [17920/50000 (40%)]\tLoss: 1.149843, Accuracy: 59.38\n",
      "Train Epoch: 2 [19200/50000 (43%)]\tLoss: 1.126659, Accuracy: 58.20\n",
      "Train Epoch: 2 [20480/50000 (45%)]\tLoss: 1.092484, Accuracy: 58.98\n",
      "Train Epoch: 2 [21760/50000 (48%)]\tLoss: 1.099942, Accuracy: 55.47\n",
      "Train Epoch: 2 [23040/50000 (51%)]\tLoss: 1.186884, Accuracy: 60.94\n",
      "Train Epoch: 2 [24320/50000 (54%)]\tLoss: 1.117447, Accuracy: 60.55\n",
      "Train Epoch: 2 [25600/50000 (57%)]\tLoss: 1.173386, Accuracy: 55.08\n",
      "Train Epoch: 2 [26880/50000 (60%)]\tLoss: 1.084559, Accuracy: 58.98\n",
      "Train Epoch: 2 [28160/50000 (62%)]\tLoss: 1.171377, Accuracy: 59.77\n",
      "Train Epoch: 2 [29440/50000 (65%)]\tLoss: 1.049761, Accuracy: 62.89\n",
      "Train Epoch: 2 [30720/50000 (68%)]\tLoss: 1.029481, Accuracy: 63.28\n",
      "Train Epoch: 2 [32000/50000 (71%)]\tLoss: 1.121746, Accuracy: 58.98\n",
      "Train Epoch: 2 [33280/50000 (74%)]\tLoss: 1.131498, Accuracy: 58.98\n",
      "Train Epoch: 2 [34560/50000 (77%)]\tLoss: 1.166869, Accuracy: 60.55\n",
      "Train Epoch: 2 [35840/50000 (80%)]\tLoss: 1.035683, Accuracy: 60.55\n",
      "Train Epoch: 2 [37120/50000 (82%)]\tLoss: 1.028708, Accuracy: 59.38\n",
      "Train Epoch: 2 [38400/50000 (85%)]\tLoss: 1.008805, Accuracy: 62.11\n",
      "Train Epoch: 2 [39680/50000 (88%)]\tLoss: 1.161276, Accuracy: 58.59\n",
      "Train Epoch: 2 [40960/50000 (91%)]\tLoss: 1.036611, Accuracy: 63.28\n",
      "Train Epoch: 2 [42240/50000 (94%)]\tLoss: 1.166182, Accuracy: 57.03\n",
      "Train Epoch: 2 [43520/50000 (97%)]\tLoss: 1.036265, Accuracy: 62.89\n",
      "Train Epoch: 2 [35000/50000 (99%)]\tLoss: 0.937140, Accuracy: 70.50\n",
      "\n",
      "Validation set: Average loss: 2.1692, Accuracy: 2482/5000 (49.00%)\n",
      "\n",
      "the time of this epoch:[21.577322244644165 s]\n",
      "Train Epoch: 3 [0/50000 (0%)]\tLoss: 1.088407, Accuracy: 61.33\n",
      "Train Epoch: 3 [1280/50000 (3%)]\tLoss: 1.053350, Accuracy: 62.89\n",
      "Train Epoch: 3 [2560/50000 (6%)]\tLoss: 1.126616, Accuracy: 57.03\n",
      "Train Epoch: 3 [3840/50000 (9%)]\tLoss: 0.988742, Accuracy: 65.23\n",
      "Train Epoch: 3 [5120/50000 (11%)]\tLoss: 1.202767, Accuracy: 57.42\n",
      "Train Epoch: 3 [6400/50000 (14%)]\tLoss: 1.000872, Accuracy: 63.67\n",
      "Train Epoch: 3 [7680/50000 (17%)]\tLoss: 0.907074, Accuracy: 67.58\n",
      "Train Epoch: 3 [8960/50000 (20%)]\tLoss: 1.005800, Accuracy: 62.11\n",
      "Train Epoch: 3 [10240/50000 (23%)]\tLoss: 0.993526, Accuracy: 66.02\n",
      "Train Epoch: 3 [11520/50000 (26%)]\tLoss: 0.856707, Accuracy: 71.48\n",
      "Train Epoch: 3 [12800/50000 (28%)]\tLoss: 1.010143, Accuracy: 61.33\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 3 [14080/50000 (31%)]\tLoss: 1.002285, Accuracy: 61.33\n",
      "Train Epoch: 3 [15360/50000 (34%)]\tLoss: 1.100897, Accuracy: 63.67\n",
      "Train Epoch: 3 [16640/50000 (37%)]\tLoss: 1.001543, Accuracy: 62.50\n",
      "Train Epoch: 3 [17920/50000 (40%)]\tLoss: 1.066111, Accuracy: 62.50\n",
      "Train Epoch: 3 [19200/50000 (43%)]\tLoss: 0.999437, Accuracy: 63.67\n",
      "Train Epoch: 3 [20480/50000 (45%)]\tLoss: 0.896160, Accuracy: 64.84\n",
      "Train Epoch: 3 [21760/50000 (48%)]\tLoss: 0.990526, Accuracy: 65.62\n",
      "Train Epoch: 3 [23040/50000 (51%)]\tLoss: 1.004177, Accuracy: 63.67\n",
      "Train Epoch: 3 [24320/50000 (54%)]\tLoss: 1.030357, Accuracy: 63.67\n",
      "Train Epoch: 3 [25600/50000 (57%)]\tLoss: 0.837519, Accuracy: 69.14\n",
      "Train Epoch: 3 [26880/50000 (60%)]\tLoss: 0.920745, Accuracy: 68.75\n",
      "Train Epoch: 3 [28160/50000 (62%)]\tLoss: 0.988273, Accuracy: 62.50\n",
      "Train Epoch: 3 [29440/50000 (65%)]\tLoss: 0.974446, Accuracy: 64.06\n",
      "Train Epoch: 3 [30720/50000 (68%)]\tLoss: 0.866317, Accuracy: 67.97\n",
      "Train Epoch: 3 [32000/50000 (71%)]\tLoss: 0.905450, Accuracy: 67.97\n",
      "Train Epoch: 3 [33280/50000 (74%)]\tLoss: 0.862284, Accuracy: 68.36\n",
      "Train Epoch: 3 [34560/50000 (77%)]\tLoss: 0.898586, Accuracy: 72.27\n",
      "Train Epoch: 3 [35840/50000 (80%)]\tLoss: 0.987406, Accuracy: 65.23\n",
      "Train Epoch: 3 [37120/50000 (82%)]\tLoss: 0.918354, Accuracy: 71.09\n",
      "Train Epoch: 3 [38400/50000 (85%)]\tLoss: 0.993837, Accuracy: 65.62\n",
      "Train Epoch: 3 [39680/50000 (88%)]\tLoss: 1.031045, Accuracy: 62.89\n",
      "Train Epoch: 3 [40960/50000 (91%)]\tLoss: 0.972070, Accuracy: 64.06\n",
      "Train Epoch: 3 [42240/50000 (94%)]\tLoss: 1.034671, Accuracy: 64.84\n",
      "Train Epoch: 3 [43520/50000 (97%)]\tLoss: 0.864036, Accuracy: 69.53\n",
      "Train Epoch: 3 [35000/50000 (99%)]\tLoss: 0.999670, Accuracy: 66.50\n",
      "\n",
      "Validation set: Average loss: 1.2990, Accuracy: 2910/5000 (58.00%)\n",
      "\n",
      "the time of this epoch:[21.537471055984497 s]\n",
      "Train Epoch: 4 [0/50000 (0%)]\tLoss: 0.880451, Accuracy: 67.58\n",
      "Train Epoch: 4 [1280/50000 (3%)]\tLoss: 0.906294, Accuracy: 67.97\n",
      "Train Epoch: 4 [2560/50000 (6%)]\tLoss: 0.816354, Accuracy: 69.92\n",
      "Train Epoch: 4 [3840/50000 (9%)]\tLoss: 0.869885, Accuracy: 67.58\n",
      "Train Epoch: 4 [5120/50000 (11%)]\tLoss: 0.813819, Accuracy: 70.31\n",
      "Train Epoch: 4 [6400/50000 (14%)]\tLoss: 0.873201, Accuracy: 67.58\n",
      "Train Epoch: 4 [7680/50000 (17%)]\tLoss: 0.960101, Accuracy: 69.14\n",
      "Train Epoch: 4 [8960/50000 (20%)]\tLoss: 0.757733, Accuracy: 75.78\n",
      "Train Epoch: 4 [10240/50000 (23%)]\tLoss: 0.828631, Accuracy: 73.44\n",
      "Train Epoch: 4 [11520/50000 (26%)]\tLoss: 0.891434, Accuracy: 67.97\n",
      "Train Epoch: 4 [12800/50000 (28%)]\tLoss: 0.952722, Accuracy: 67.58\n",
      "Train Epoch: 4 [14080/50000 (31%)]\tLoss: 0.793139, Accuracy: 73.44\n",
      "Train Epoch: 4 [15360/50000 (34%)]\tLoss: 0.830277, Accuracy: 70.70\n",
      "Train Epoch: 4 [16640/50000 (37%)]\tLoss: 0.901904, Accuracy: 69.53\n",
      "Train Epoch: 4 [17920/50000 (40%)]\tLoss: 0.800359, Accuracy: 71.09\n",
      "Train Epoch: 4 [19200/50000 (43%)]\tLoss: 0.862231, Accuracy: 69.53\n",
      "Train Epoch: 4 [20480/50000 (45%)]\tLoss: 0.763917, Accuracy: 70.31\n",
      "Train Epoch: 4 [21760/50000 (48%)]\tLoss: 0.933345, Accuracy: 62.50\n",
      "Train Epoch: 4 [23040/50000 (51%)]\tLoss: 0.621410, Accuracy: 81.25\n",
      "Train Epoch: 4 [24320/50000 (54%)]\tLoss: 0.832428, Accuracy: 71.48\n",
      "Train Epoch: 4 [25600/50000 (57%)]\tLoss: 0.960089, Accuracy: 65.23\n",
      "Train Epoch: 4 [26880/50000 (60%)]\tLoss: 0.755099, Accuracy: 73.44\n",
      "Train Epoch: 4 [28160/50000 (62%)]\tLoss: 0.851348, Accuracy: 69.14\n",
      "Train Epoch: 4 [29440/50000 (65%)]\tLoss: 0.799857, Accuracy: 76.56\n",
      "Train Epoch: 4 [30720/50000 (68%)]\tLoss: 0.830959, Accuracy: 72.66\n",
      "Train Epoch: 4 [32000/50000 (71%)]\tLoss: 0.900016, Accuracy: 72.27\n",
      "Train Epoch: 4 [33280/50000 (74%)]\tLoss: 0.780591, Accuracy: 73.83\n",
      "Train Epoch: 4 [34560/50000 (77%)]\tLoss: 0.680309, Accuracy: 78.91\n",
      "Train Epoch: 4 [35840/50000 (80%)]\tLoss: 0.830967, Accuracy: 72.66\n",
      "Train Epoch: 4 [37120/50000 (82%)]\tLoss: 0.807129, Accuracy: 71.09\n",
      "Train Epoch: 4 [38400/50000 (85%)]\tLoss: 0.853248, Accuracy: 69.92\n",
      "Train Epoch: 4 [39680/50000 (88%)]\tLoss: 0.724089, Accuracy: 74.61\n",
      "Train Epoch: 4 [40960/50000 (91%)]\tLoss: 0.864069, Accuracy: 69.53\n",
      "Train Epoch: 4 [42240/50000 (94%)]\tLoss: 0.785517, Accuracy: 74.22\n",
      "Train Epoch: 4 [43520/50000 (97%)]\tLoss: 0.862304, Accuracy: 67.97\n",
      "Train Epoch: 4 [35000/50000 (99%)]\tLoss: 0.853841, Accuracy: 70.50\n",
      "\n",
      "Validation set: Average loss: 1.2885, Accuracy: 3053/5000 (61.00%)\n",
      "\n",
      "the time of this epoch:[21.536515474319458 s]\n",
      "Train Epoch: 5 [0/50000 (0%)]\tLoss: 0.794806, Accuracy: 73.44\n",
      "Train Epoch: 5 [1280/50000 (3%)]\tLoss: 0.851460, Accuracy: 70.31\n",
      "Train Epoch: 5 [2560/50000 (6%)]\tLoss: 0.843097, Accuracy: 69.14\n",
      "Train Epoch: 5 [3840/50000 (9%)]\tLoss: 0.753557, Accuracy: 74.61\n",
      "Train Epoch: 5 [5120/50000 (11%)]\tLoss: 0.769185, Accuracy: 74.61\n",
      "Train Epoch: 5 [6400/50000 (14%)]\tLoss: 0.718109, Accuracy: 71.48\n",
      "Train Epoch: 5 [7680/50000 (17%)]\tLoss: 0.713652, Accuracy: 76.17\n",
      "Train Epoch: 5 [8960/50000 (20%)]\tLoss: 0.730363, Accuracy: 76.56\n",
      "Train Epoch: 5 [10240/50000 (23%)]\tLoss: 0.780041, Accuracy: 72.27\n",
      "Train Epoch: 5 [11520/50000 (26%)]\tLoss: 0.744795, Accuracy: 70.70\n",
      "Train Epoch: 5 [12800/50000 (28%)]\tLoss: 0.743733, Accuracy: 73.83\n",
      "Train Epoch: 5 [14080/50000 (31%)]\tLoss: 0.821686, Accuracy: 70.31\n",
      "Train Epoch: 5 [15360/50000 (34%)]\tLoss: 0.702952, Accuracy: 75.39\n",
      "Train Epoch: 5 [16640/50000 (37%)]\tLoss: 0.844139, Accuracy: 70.31\n",
      "Train Epoch: 5 [17920/50000 (40%)]\tLoss: 0.836127, Accuracy: 70.31\n",
      "Train Epoch: 5 [19200/50000 (43%)]\tLoss: 0.821969, Accuracy: 71.88\n",
      "Train Epoch: 5 [20480/50000 (45%)]\tLoss: 0.680590, Accuracy: 80.08\n",
      "Train Epoch: 5 [21760/50000 (48%)]\tLoss: 0.731296, Accuracy: 75.78\n",
      "Train Epoch: 5 [23040/50000 (51%)]\tLoss: 0.730204, Accuracy: 75.00\n",
      "Train Epoch: 5 [24320/50000 (54%)]\tLoss: 0.777306, Accuracy: 73.83\n",
      "Train Epoch: 5 [25600/50000 (57%)]\tLoss: 0.837264, Accuracy: 67.97\n",
      "Train Epoch: 5 [26880/50000 (60%)]\tLoss: 0.748074, Accuracy: 75.00\n",
      "Train Epoch: 5 [28160/50000 (62%)]\tLoss: 0.743295, Accuracy: 73.83\n",
      "Train Epoch: 5 [29440/50000 (65%)]\tLoss: 0.784270, Accuracy: 75.00\n",
      "Train Epoch: 5 [30720/50000 (68%)]\tLoss: 0.673974, Accuracy: 74.22\n",
      "Train Epoch: 5 [32000/50000 (71%)]\tLoss: 0.747311, Accuracy: 72.27\n",
      "Train Epoch: 5 [33280/50000 (74%)]\tLoss: 0.847182, Accuracy: 74.22\n",
      "Train Epoch: 5 [34560/50000 (77%)]\tLoss: 0.843287, Accuracy: 69.14\n",
      "Train Epoch: 5 [35840/50000 (80%)]\tLoss: 0.723014, Accuracy: 77.34\n",
      "Train Epoch: 5 [37120/50000 (82%)]\tLoss: 0.812581, Accuracy: 70.31\n",
      "Train Epoch: 5 [38400/50000 (85%)]\tLoss: 0.679860, Accuracy: 74.22\n",
      "Train Epoch: 5 [39680/50000 (88%)]\tLoss: 0.797874, Accuracy: 67.58\n",
      "Train Epoch: 5 [40960/50000 (91%)]\tLoss: 0.779599, Accuracy: 74.22\n",
      "Train Epoch: 5 [42240/50000 (94%)]\tLoss: 0.728598, Accuracy: 75.39\n",
      "Train Epoch: 5 [43520/50000 (97%)]\tLoss: 0.753491, Accuracy: 76.17\n",
      "Train Epoch: 5 [35000/50000 (99%)]\tLoss: 0.694176, Accuracy: 73.50\n",
      "\n",
      "Validation set: Average loss: 0.8488, Accuracy: 3562/5000 (71.00%)\n",
      "\n",
      "the time of this epoch:[21.556759357452393 s]\n",
      "Train Epoch: 6 [0/50000 (0%)]\tLoss: 0.747540, Accuracy: 72.27\n",
      "Train Epoch: 6 [1280/50000 (3%)]\tLoss: 0.579382, Accuracy: 79.69\n",
      "Train Epoch: 6 [2560/50000 (6%)]\tLoss: 0.714935, Accuracy: 73.44\n",
      "Train Epoch: 6 [3840/50000 (9%)]\tLoss: 0.630842, Accuracy: 76.95\n",
      "Train Epoch: 6 [5120/50000 (11%)]\tLoss: 0.654944, Accuracy: 78.12\n",
      "Train Epoch: 6 [6400/50000 (14%)]\tLoss: 0.645728, Accuracy: 77.73\n",
      "Train Epoch: 6 [7680/50000 (17%)]\tLoss: 0.696997, Accuracy: 77.34\n",
      "Train Epoch: 6 [8960/50000 (20%)]\tLoss: 0.643329, Accuracy: 77.73\n",
      "Train Epoch: 6 [10240/50000 (23%)]\tLoss: 0.705803, Accuracy: 73.05\n",
      "Train Epoch: 6 [11520/50000 (26%)]\tLoss: 0.608137, Accuracy: 80.47\n",
      "Train Epoch: 6 [12800/50000 (28%)]\tLoss: 0.636053, Accuracy: 78.91\n",
      "Train Epoch: 6 [14080/50000 (31%)]\tLoss: 0.813692, Accuracy: 72.66\n",
      "Train Epoch: 6 [15360/50000 (34%)]\tLoss: 0.756281, Accuracy: 76.56\n",
      "Train Epoch: 6 [16640/50000 (37%)]\tLoss: 0.759458, Accuracy: 75.00\n",
      "Train Epoch: 6 [17920/50000 (40%)]\tLoss: 0.816839, Accuracy: 73.44\n",
      "Train Epoch: 6 [19200/50000 (43%)]\tLoss: 0.726478, Accuracy: 77.34\n",
      "Train Epoch: 6 [20480/50000 (45%)]\tLoss: 0.659545, Accuracy: 76.95\n",
      "Train Epoch: 6 [21760/50000 (48%)]\tLoss: 0.728524, Accuracy: 76.56\n",
      "Train Epoch: 6 [23040/50000 (51%)]\tLoss: 0.795550, Accuracy: 75.39\n",
      "Train Epoch: 6 [24320/50000 (54%)]\tLoss: 0.635386, Accuracy: 78.52\n",
      "Train Epoch: 6 [25600/50000 (57%)]\tLoss: 0.840354, Accuracy: 70.31\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 6 [26880/50000 (60%)]\tLoss: 0.704397, Accuracy: 76.17\n",
      "Train Epoch: 6 [28160/50000 (62%)]\tLoss: 0.739517, Accuracy: 72.27\n",
      "Train Epoch: 6 [29440/50000 (65%)]\tLoss: 0.671808, Accuracy: 75.39\n",
      "Train Epoch: 6 [30720/50000 (68%)]\tLoss: 0.717396, Accuracy: 75.00\n",
      "Train Epoch: 6 [32000/50000 (71%)]\tLoss: 0.702695, Accuracy: 73.44\n",
      "Train Epoch: 6 [33280/50000 (74%)]\tLoss: 0.789652, Accuracy: 75.39\n",
      "Train Epoch: 6 [34560/50000 (77%)]\tLoss: 0.763403, Accuracy: 72.27\n",
      "Train Epoch: 6 [35840/50000 (80%)]\tLoss: 0.790211, Accuracy: 75.00\n",
      "Train Epoch: 6 [37120/50000 (82%)]\tLoss: 0.731040, Accuracy: 75.78\n",
      "Train Epoch: 6 [38400/50000 (85%)]\tLoss: 0.748385, Accuracy: 75.78\n",
      "Train Epoch: 6 [39680/50000 (88%)]\tLoss: 0.784371, Accuracy: 71.88\n",
      "Train Epoch: 6 [40960/50000 (91%)]\tLoss: 0.544778, Accuracy: 82.03\n",
      "Train Epoch: 6 [42240/50000 (94%)]\tLoss: 0.620572, Accuracy: 77.34\n",
      "Train Epoch: 6 [43520/50000 (97%)]\tLoss: 0.601540, Accuracy: 78.52\n",
      "Train Epoch: 6 [35000/50000 (99%)]\tLoss: 0.689037, Accuracy: 76.00\n",
      "\n",
      "Validation set: Average loss: 0.8233, Accuracy: 3689/5000 (73.00%)\n",
      "\n",
      "the time of this epoch:[21.47383141517639 s]\n",
      "Train Epoch: 7 [0/50000 (0%)]\tLoss: 0.657164, Accuracy: 76.17\n",
      "Train Epoch: 7 [1280/50000 (3%)]\tLoss: 0.715652, Accuracy: 75.39\n",
      "Train Epoch: 7 [2560/50000 (6%)]\tLoss: 0.592853, Accuracy: 80.08\n",
      "Train Epoch: 7 [3840/50000 (9%)]\tLoss: 0.614449, Accuracy: 78.12\n",
      "Train Epoch: 7 [5120/50000 (11%)]\tLoss: 0.739613, Accuracy: 75.39\n",
      "Train Epoch: 7 [6400/50000 (14%)]\tLoss: 0.554056, Accuracy: 81.64\n",
      "Train Epoch: 7 [7680/50000 (17%)]\tLoss: 0.670418, Accuracy: 75.39\n",
      "Train Epoch: 7 [8960/50000 (20%)]\tLoss: 0.624991, Accuracy: 78.91\n",
      "Train Epoch: 7 [10240/50000 (23%)]\tLoss: 0.641623, Accuracy: 80.86\n",
      "Train Epoch: 7 [11520/50000 (26%)]\tLoss: 0.766402, Accuracy: 76.95\n",
      "Train Epoch: 7 [12800/50000 (28%)]\tLoss: 0.662986, Accuracy: 78.12\n",
      "Train Epoch: 7 [14080/50000 (31%)]\tLoss: 0.500786, Accuracy: 82.81\n",
      "Train Epoch: 7 [15360/50000 (34%)]\tLoss: 0.603635, Accuracy: 76.56\n",
      "Train Epoch: 7 [16640/50000 (37%)]\tLoss: 0.628476, Accuracy: 75.00\n",
      "Train Epoch: 7 [17920/50000 (40%)]\tLoss: 0.701675, Accuracy: 75.78\n",
      "Train Epoch: 7 [19200/50000 (43%)]\tLoss: 0.703761, Accuracy: 74.61\n",
      "Train Epoch: 7 [20480/50000 (45%)]\tLoss: 0.660177, Accuracy: 78.12\n",
      "Train Epoch: 7 [21760/50000 (48%)]\tLoss: 0.695146, Accuracy: 75.39\n",
      "Train Epoch: 7 [23040/50000 (51%)]\tLoss: 0.751128, Accuracy: 75.39\n",
      "Train Epoch: 7 [24320/50000 (54%)]\tLoss: 0.568297, Accuracy: 82.42\n",
      "Train Epoch: 7 [25600/50000 (57%)]\tLoss: 0.565566, Accuracy: 82.03\n",
      "Train Epoch: 7 [26880/50000 (60%)]\tLoss: 0.636180, Accuracy: 79.69\n",
      "Train Epoch: 7 [28160/50000 (62%)]\tLoss: 0.733164, Accuracy: 75.78\n",
      "Train Epoch: 7 [29440/50000 (65%)]\tLoss: 0.682317, Accuracy: 76.56\n",
      "Train Epoch: 7 [30720/50000 (68%)]\tLoss: 0.564797, Accuracy: 80.47\n",
      "Train Epoch: 7 [32000/50000 (71%)]\tLoss: 0.670790, Accuracy: 76.56\n",
      "Train Epoch: 7 [33280/50000 (74%)]\tLoss: 0.661565, Accuracy: 79.69\n",
      "Train Epoch: 7 [34560/50000 (77%)]\tLoss: 0.578764, Accuracy: 76.95\n",
      "Train Epoch: 7 [35840/50000 (80%)]\tLoss: 0.632995, Accuracy: 80.86\n",
      "Train Epoch: 7 [37120/50000 (82%)]\tLoss: 0.592353, Accuracy: 82.42\n",
      "Train Epoch: 7 [38400/50000 (85%)]\tLoss: 0.721696, Accuracy: 75.39\n",
      "Train Epoch: 7 [39680/50000 (88%)]\tLoss: 0.560807, Accuracy: 80.86\n",
      "Train Epoch: 7 [40960/50000 (91%)]\tLoss: 0.594724, Accuracy: 76.95\n",
      "Train Epoch: 7 [42240/50000 (94%)]\tLoss: 0.693314, Accuracy: 75.78\n",
      "Train Epoch: 7 [43520/50000 (97%)]\tLoss: 0.606621, Accuracy: 80.08\n",
      "Train Epoch: 7 [35000/50000 (99%)]\tLoss: 0.607506, Accuracy: 81.50\n",
      "\n",
      "Validation set: Average loss: 0.8505, Accuracy: 3610/5000 (72.00%)\n",
      "\n",
      "the time of this epoch:[21.41931700706482 s]\n",
      "Train Epoch: 8 [0/50000 (0%)]\tLoss: 0.516854, Accuracy: 83.98\n",
      "Train Epoch: 8 [1280/50000 (3%)]\tLoss: 0.590746, Accuracy: 79.30\n",
      "Train Epoch: 8 [2560/50000 (6%)]\tLoss: 0.543082, Accuracy: 80.86\n",
      "Train Epoch: 8 [3840/50000 (9%)]\tLoss: 0.596726, Accuracy: 78.12\n",
      "Train Epoch: 8 [5120/50000 (11%)]\tLoss: 0.505754, Accuracy: 80.86\n",
      "Train Epoch: 8 [6400/50000 (14%)]\tLoss: 0.695386, Accuracy: 76.95\n",
      "Train Epoch: 8 [7680/50000 (17%)]\tLoss: 0.550162, Accuracy: 83.20\n",
      "Train Epoch: 8 [8960/50000 (20%)]\tLoss: 0.555879, Accuracy: 81.25\n",
      "Train Epoch: 8 [10240/50000 (23%)]\tLoss: 0.595102, Accuracy: 82.03\n",
      "Train Epoch: 8 [11520/50000 (26%)]\tLoss: 0.610712, Accuracy: 81.64\n",
      "Train Epoch: 8 [12800/50000 (28%)]\tLoss: 0.637558, Accuracy: 78.91\n",
      "Train Epoch: 8 [14080/50000 (31%)]\tLoss: 0.691320, Accuracy: 76.95\n",
      "Train Epoch: 8 [15360/50000 (34%)]\tLoss: 0.526685, Accuracy: 82.03\n",
      "Train Epoch: 8 [16640/50000 (37%)]\tLoss: 0.619998, Accuracy: 78.52\n",
      "Train Epoch: 8 [17920/50000 (40%)]\tLoss: 0.477029, Accuracy: 80.08\n",
      "Train Epoch: 8 [19200/50000 (43%)]\tLoss: 0.556587, Accuracy: 80.47\n",
      "Train Epoch: 8 [20480/50000 (45%)]\tLoss: 0.592621, Accuracy: 79.30\n",
      "Train Epoch: 8 [21760/50000 (48%)]\tLoss: 0.565273, Accuracy: 79.69\n",
      "Train Epoch: 8 [23040/50000 (51%)]\tLoss: 0.589538, Accuracy: 76.95\n",
      "Train Epoch: 8 [24320/50000 (54%)]\tLoss: 0.629432, Accuracy: 79.69\n",
      "Train Epoch: 8 [25600/50000 (57%)]\tLoss: 0.523148, Accuracy: 81.64\n",
      "Train Epoch: 8 [26880/50000 (60%)]\tLoss: 0.567549, Accuracy: 79.69\n",
      "Train Epoch: 8 [28160/50000 (62%)]\tLoss: 0.525627, Accuracy: 82.42\n",
      "Train Epoch: 8 [29440/50000 (65%)]\tLoss: 0.556699, Accuracy: 80.08\n",
      "Train Epoch: 8 [30720/50000 (68%)]\tLoss: 0.619788, Accuracy: 78.52\n",
      "Train Epoch: 8 [32000/50000 (71%)]\tLoss: 0.588494, Accuracy: 78.52\n",
      "Train Epoch: 8 [33280/50000 (74%)]\tLoss: 0.605897, Accuracy: 80.08\n",
      "Train Epoch: 8 [34560/50000 (77%)]\tLoss: 0.628305, Accuracy: 77.73\n",
      "Train Epoch: 8 [35840/50000 (80%)]\tLoss: 0.514947, Accuracy: 80.08\n",
      "Train Epoch: 8 [37120/50000 (82%)]\tLoss: 0.588652, Accuracy: 82.03\n",
      "Train Epoch: 8 [38400/50000 (85%)]\tLoss: 0.598061, Accuracy: 77.73\n",
      "Train Epoch: 8 [39680/50000 (88%)]\tLoss: 0.639884, Accuracy: 75.00\n",
      "Train Epoch: 8 [40960/50000 (91%)]\tLoss: 0.628978, Accuracy: 78.12\n",
      "Train Epoch: 8 [42240/50000 (94%)]\tLoss: 0.541691, Accuracy: 83.59\n",
      "Train Epoch: 8 [43520/50000 (97%)]\tLoss: 0.565613, Accuracy: 81.25\n",
      "Train Epoch: 8 [35000/50000 (99%)]\tLoss: 0.444641, Accuracy: 87.00\n",
      "\n",
      "Validation set: Average loss: 0.7345, Accuracy: 3750/5000 (75.00%)\n",
      "\n",
      "the time of this epoch:[21.481847047805786 s]\n",
      "Train Epoch: 9 [0/50000 (0%)]\tLoss: 0.573385, Accuracy: 82.03\n",
      "Train Epoch: 9 [1280/50000 (3%)]\tLoss: 0.477315, Accuracy: 86.33\n",
      "Train Epoch: 9 [2560/50000 (6%)]\tLoss: 0.645453, Accuracy: 76.17\n",
      "Train Epoch: 9 [3840/50000 (9%)]\tLoss: 0.541146, Accuracy: 82.03\n",
      "Train Epoch: 9 [5120/50000 (11%)]\tLoss: 0.528093, Accuracy: 80.86\n",
      "Train Epoch: 9 [6400/50000 (14%)]\tLoss: 0.515641, Accuracy: 78.52\n",
      "Train Epoch: 9 [7680/50000 (17%)]\tLoss: 0.527377, Accuracy: 82.03\n",
      "Train Epoch: 9 [8960/50000 (20%)]\tLoss: 0.568079, Accuracy: 80.86\n",
      "Train Epoch: 9 [10240/50000 (23%)]\tLoss: 0.578552, Accuracy: 80.47\n",
      "Train Epoch: 9 [11520/50000 (26%)]\tLoss: 0.597635, Accuracy: 80.08\n",
      "Train Epoch: 9 [12800/50000 (28%)]\tLoss: 0.635135, Accuracy: 77.34\n",
      "Train Epoch: 9 [14080/50000 (31%)]\tLoss: 0.644308, Accuracy: 78.52\n",
      "Train Epoch: 9 [15360/50000 (34%)]\tLoss: 0.576641, Accuracy: 80.08\n",
      "Train Epoch: 9 [16640/50000 (37%)]\tLoss: 0.491632, Accuracy: 82.81\n",
      "Train Epoch: 9 [17920/50000 (40%)]\tLoss: 0.590092, Accuracy: 80.47\n",
      "Train Epoch: 9 [19200/50000 (43%)]\tLoss: 0.522764, Accuracy: 83.59\n",
      "Train Epoch: 9 [20480/50000 (45%)]\tLoss: 0.582187, Accuracy: 81.64\n",
      "Train Epoch: 9 [21760/50000 (48%)]\tLoss: 0.494427, Accuracy: 81.64\n",
      "Train Epoch: 9 [23040/50000 (51%)]\tLoss: 0.504543, Accuracy: 82.03\n",
      "Train Epoch: 9 [24320/50000 (54%)]\tLoss: 0.599857, Accuracy: 81.25\n",
      "Train Epoch: 9 [25600/50000 (57%)]\tLoss: 0.609997, Accuracy: 78.91\n",
      "Train Epoch: 9 [26880/50000 (60%)]\tLoss: 0.591585, Accuracy: 79.69\n",
      "Train Epoch: 9 [28160/50000 (62%)]\tLoss: 0.584392, Accuracy: 80.47\n",
      "Train Epoch: 9 [29440/50000 (65%)]\tLoss: 0.579340, Accuracy: 80.47\n",
      "Train Epoch: 9 [30720/50000 (68%)]\tLoss: 0.685152, Accuracy: 77.73\n",
      "Train Epoch: 9 [32000/50000 (71%)]\tLoss: 0.500362, Accuracy: 85.94\n",
      "Train Epoch: 9 [33280/50000 (74%)]\tLoss: 0.640331, Accuracy: 75.78\n",
      "Train Epoch: 9 [34560/50000 (77%)]\tLoss: 0.478662, Accuracy: 83.98\n",
      "Train Epoch: 9 [35840/50000 (80%)]\tLoss: 0.569189, Accuracy: 82.42\n",
      "Train Epoch: 9 [37120/50000 (82%)]\tLoss: 0.584087, Accuracy: 80.47\n",
      "Train Epoch: 9 [38400/50000 (85%)]\tLoss: 0.466918, Accuracy: 84.77\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 9 [39680/50000 (88%)]\tLoss: 0.559870, Accuracy: 80.08\n",
      "Train Epoch: 9 [40960/50000 (91%)]\tLoss: 0.501429, Accuracy: 85.16\n",
      "Train Epoch: 9 [42240/50000 (94%)]\tLoss: 0.604673, Accuracy: 81.25\n",
      "Train Epoch: 9 [43520/50000 (97%)]\tLoss: 0.631826, Accuracy: 78.91\n",
      "Train Epoch: 9 [35000/50000 (99%)]\tLoss: 0.523867, Accuracy: 82.50\n",
      "\n",
      "Validation set: Average loss: 0.6508, Accuracy: 3936/5000 (78.00%)\n",
      "\n",
      "the time of this epoch:[21.43558931350708 s]\n",
      "Train Epoch: 10 [0/50000 (0%)]\tLoss: 0.698342, Accuracy: 76.17\n",
      "Train Epoch: 10 [1280/50000 (3%)]\tLoss: 0.479366, Accuracy: 83.59\n",
      "Train Epoch: 10 [2560/50000 (6%)]\tLoss: 0.473839, Accuracy: 81.64\n",
      "Train Epoch: 10 [3840/50000 (9%)]\tLoss: 0.513023, Accuracy: 83.98\n",
      "Train Epoch: 10 [5120/50000 (11%)]\tLoss: 0.514213, Accuracy: 83.20\n",
      "Train Epoch: 10 [6400/50000 (14%)]\tLoss: 0.463158, Accuracy: 83.20\n",
      "Train Epoch: 10 [7680/50000 (17%)]\tLoss: 0.553520, Accuracy: 81.25\n",
      "Train Epoch: 10 [8960/50000 (20%)]\tLoss: 0.540901, Accuracy: 82.42\n",
      "Train Epoch: 10 [10240/50000 (23%)]\tLoss: 0.602835, Accuracy: 79.30\n",
      "Train Epoch: 10 [11520/50000 (26%)]\tLoss: 0.472830, Accuracy: 83.98\n",
      "Train Epoch: 10 [12800/50000 (28%)]\tLoss: 0.556701, Accuracy: 80.08\n",
      "Train Epoch: 10 [14080/50000 (31%)]\tLoss: 0.509061, Accuracy: 83.98\n",
      "Train Epoch: 10 [15360/50000 (34%)]\tLoss: 0.543503, Accuracy: 82.81\n",
      "Train Epoch: 10 [16640/50000 (37%)]\tLoss: 0.487707, Accuracy: 82.81\n",
      "Train Epoch: 10 [17920/50000 (40%)]\tLoss: 0.473625, Accuracy: 82.03\n",
      "Train Epoch: 10 [19200/50000 (43%)]\tLoss: 0.628456, Accuracy: 80.86\n",
      "Train Epoch: 10 [20480/50000 (45%)]\tLoss: 0.507531, Accuracy: 81.25\n",
      "Train Epoch: 10 [21760/50000 (48%)]\tLoss: 0.480028, Accuracy: 82.42\n",
      "Train Epoch: 10 [23040/50000 (51%)]\tLoss: 0.606556, Accuracy: 78.91\n",
      "Train Epoch: 10 [24320/50000 (54%)]\tLoss: 0.647531, Accuracy: 77.34\n",
      "Train Epoch: 10 [25600/50000 (57%)]\tLoss: 0.573275, Accuracy: 79.69\n",
      "Train Epoch: 10 [26880/50000 (60%)]\tLoss: 0.563822, Accuracy: 82.81\n",
      "Train Epoch: 10 [28160/50000 (62%)]\tLoss: 0.587875, Accuracy: 81.64\n",
      "Train Epoch: 10 [29440/50000 (65%)]\tLoss: 0.554026, Accuracy: 82.42\n",
      "Train Epoch: 10 [30720/50000 (68%)]\tLoss: 0.587525, Accuracy: 79.30\n",
      "Train Epoch: 10 [32000/50000 (71%)]\tLoss: 0.621239, Accuracy: 79.69\n",
      "Train Epoch: 10 [33280/50000 (74%)]\tLoss: 0.477427, Accuracy: 85.94\n",
      "Train Epoch: 10 [34560/50000 (77%)]\tLoss: 0.502512, Accuracy: 82.81\n",
      "Train Epoch: 10 [35840/50000 (80%)]\tLoss: 0.592441, Accuracy: 80.47\n",
      "Train Epoch: 10 [37120/50000 (82%)]\tLoss: 0.530640, Accuracy: 83.20\n",
      "Train Epoch: 10 [38400/50000 (85%)]\tLoss: 0.545331, Accuracy: 82.81\n",
      "Train Epoch: 10 [39680/50000 (88%)]\tLoss: 0.527348, Accuracy: 84.38\n",
      "Train Epoch: 10 [40960/50000 (91%)]\tLoss: 0.520346, Accuracy: 83.59\n",
      "Train Epoch: 10 [42240/50000 (94%)]\tLoss: 0.485321, Accuracy: 83.59\n",
      "Train Epoch: 10 [43520/50000 (97%)]\tLoss: 0.441646, Accuracy: 84.38\n",
      "Train Epoch: 10 [35000/50000 (99%)]\tLoss: 0.621111, Accuracy: 77.50\n",
      "\n",
      "Validation set: Average loss: 0.7685, Accuracy: 3768/5000 (75.00%)\n",
      "\n",
      "the time of this epoch:[21.424914121627808 s]\n",
      "Train Epoch: 11 [0/50000 (0%)]\tLoss: 0.455646, Accuracy: 83.98\n",
      "Train Epoch: 11 [1280/50000 (3%)]\tLoss: 0.487672, Accuracy: 82.81\n",
      "Train Epoch: 11 [2560/50000 (6%)]\tLoss: 0.544636, Accuracy: 80.08\n",
      "Train Epoch: 11 [3840/50000 (9%)]\tLoss: 0.627545, Accuracy: 78.12\n",
      "Train Epoch: 11 [5120/50000 (11%)]\tLoss: 0.483849, Accuracy: 84.38\n",
      "Train Epoch: 11 [6400/50000 (14%)]\tLoss: 0.510375, Accuracy: 83.98\n",
      "Train Epoch: 11 [7680/50000 (17%)]\tLoss: 0.494109, Accuracy: 82.81\n",
      "Train Epoch: 11 [8960/50000 (20%)]\tLoss: 0.509213, Accuracy: 82.03\n",
      "Train Epoch: 11 [10240/50000 (23%)]\tLoss: 0.423057, Accuracy: 86.72\n",
      "Train Epoch: 11 [11520/50000 (26%)]\tLoss: 0.516678, Accuracy: 82.03\n",
      "Train Epoch: 11 [12800/50000 (28%)]\tLoss: 0.456374, Accuracy: 84.38\n",
      "Train Epoch: 11 [14080/50000 (31%)]\tLoss: 0.581711, Accuracy: 79.30\n",
      "Train Epoch: 11 [15360/50000 (34%)]\tLoss: 0.576797, Accuracy: 83.59\n",
      "Train Epoch: 11 [16640/50000 (37%)]\tLoss: 0.488303, Accuracy: 83.20\n",
      "Train Epoch: 11 [17920/50000 (40%)]\tLoss: 0.411617, Accuracy: 85.55\n",
      "Train Epoch: 11 [19200/50000 (43%)]\tLoss: 0.519750, Accuracy: 84.38\n",
      "Train Epoch: 11 [20480/50000 (45%)]\tLoss: 0.578601, Accuracy: 81.25\n",
      "Train Epoch: 11 [21760/50000 (48%)]\tLoss: 0.604158, Accuracy: 80.08\n",
      "Train Epoch: 11 [23040/50000 (51%)]\tLoss: 0.528271, Accuracy: 83.59\n",
      "Train Epoch: 11 [24320/50000 (54%)]\tLoss: 0.542340, Accuracy: 81.64\n",
      "Train Epoch: 11 [25600/50000 (57%)]\tLoss: 0.429030, Accuracy: 85.94\n",
      "Train Epoch: 11 [26880/50000 (60%)]\tLoss: 0.534430, Accuracy: 83.59\n",
      "Train Epoch: 11 [28160/50000 (62%)]\tLoss: 0.549360, Accuracy: 81.64\n",
      "Train Epoch: 11 [29440/50000 (65%)]\tLoss: 0.483513, Accuracy: 84.38\n",
      "Train Epoch: 11 [30720/50000 (68%)]\tLoss: 0.586977, Accuracy: 79.30\n",
      "Train Epoch: 11 [32000/50000 (71%)]\tLoss: 0.430387, Accuracy: 84.77\n",
      "Train Epoch: 11 [33280/50000 (74%)]\tLoss: 0.533193, Accuracy: 81.25\n",
      "Train Epoch: 11 [34560/50000 (77%)]\tLoss: 0.490124, Accuracy: 82.81\n",
      "Train Epoch: 11 [35840/50000 (80%)]\tLoss: 0.557572, Accuracy: 79.30\n",
      "Train Epoch: 11 [37120/50000 (82%)]\tLoss: 0.556276, Accuracy: 81.25\n",
      "Train Epoch: 11 [38400/50000 (85%)]\tLoss: 0.524989, Accuracy: 83.98\n",
      "Train Epoch: 11 [39680/50000 (88%)]\tLoss: 0.614337, Accuracy: 79.30\n",
      "Train Epoch: 11 [40960/50000 (91%)]\tLoss: 0.502092, Accuracy: 80.47\n",
      "Train Epoch: 11 [42240/50000 (94%)]\tLoss: 0.552193, Accuracy: 82.81\n",
      "Train Epoch: 11 [43520/50000 (97%)]\tLoss: 0.508861, Accuracy: 82.42\n",
      "Train Epoch: 11 [35000/50000 (99%)]\tLoss: 0.346237, Accuracy: 89.50\n",
      "\n",
      "Validation set: Average loss: 0.5634, Accuracy: 4017/5000 (80.00%)\n",
      "\n",
      "the time of this epoch:[21.426082849502563 s]\n",
      "Train Epoch: 12 [0/50000 (0%)]\tLoss: 0.421679, Accuracy: 85.16\n",
      "Train Epoch: 12 [1280/50000 (3%)]\tLoss: 0.497537, Accuracy: 83.20\n",
      "Train Epoch: 12 [2560/50000 (6%)]\tLoss: 0.509383, Accuracy: 84.38\n",
      "Train Epoch: 12 [3840/50000 (9%)]\tLoss: 0.404828, Accuracy: 83.59\n",
      "Train Epoch: 12 [5120/50000 (11%)]\tLoss: 0.508577, Accuracy: 81.64\n",
      "Train Epoch: 12 [6400/50000 (14%)]\tLoss: 0.489862, Accuracy: 82.03\n",
      "Train Epoch: 12 [7680/50000 (17%)]\tLoss: 0.483279, Accuracy: 83.98\n",
      "Train Epoch: 12 [8960/50000 (20%)]\tLoss: 0.491274, Accuracy: 80.86\n",
      "Train Epoch: 12 [10240/50000 (23%)]\tLoss: 0.392795, Accuracy: 87.50\n",
      "Train Epoch: 12 [11520/50000 (26%)]\tLoss: 0.564651, Accuracy: 83.98\n",
      "Train Epoch: 12 [12800/50000 (28%)]\tLoss: 0.490556, Accuracy: 83.98\n",
      "Train Epoch: 12 [14080/50000 (31%)]\tLoss: 0.496914, Accuracy: 83.59\n",
      "Train Epoch: 12 [15360/50000 (34%)]\tLoss: 0.455425, Accuracy: 85.16\n",
      "Train Epoch: 12 [16640/50000 (37%)]\tLoss: 0.523030, Accuracy: 82.03\n",
      "Train Epoch: 12 [17920/50000 (40%)]\tLoss: 0.451107, Accuracy: 83.59\n",
      "Train Epoch: 12 [19200/50000 (43%)]\tLoss: 0.506921, Accuracy: 81.64\n",
      "Train Epoch: 12 [20480/50000 (45%)]\tLoss: 0.543696, Accuracy: 80.86\n",
      "Train Epoch: 12 [21760/50000 (48%)]\tLoss: 0.539657, Accuracy: 80.47\n",
      "Train Epoch: 12 [23040/50000 (51%)]\tLoss: 0.444854, Accuracy: 85.16\n",
      "Train Epoch: 12 [24320/50000 (54%)]\tLoss: 0.569426, Accuracy: 79.30\n",
      "Train Epoch: 12 [25600/50000 (57%)]\tLoss: 0.600935, Accuracy: 78.91\n",
      "Train Epoch: 12 [26880/50000 (60%)]\tLoss: 0.548276, Accuracy: 82.42\n",
      "Train Epoch: 12 [28160/50000 (62%)]\tLoss: 0.543498, Accuracy: 83.20\n",
      "Train Epoch: 12 [29440/50000 (65%)]\tLoss: 0.494284, Accuracy: 85.16\n",
      "Train Epoch: 12 [30720/50000 (68%)]\tLoss: 0.544868, Accuracy: 80.47\n",
      "Train Epoch: 12 [32000/50000 (71%)]\tLoss: 0.500233, Accuracy: 83.98\n",
      "Train Epoch: 12 [33280/50000 (74%)]\tLoss: 0.513360, Accuracy: 81.64\n",
      "Train Epoch: 12 [34560/50000 (77%)]\tLoss: 0.476898, Accuracy: 86.33\n",
      "Train Epoch: 12 [35840/50000 (80%)]\tLoss: 0.523191, Accuracy: 81.25\n",
      "Train Epoch: 12 [37120/50000 (82%)]\tLoss: 0.425032, Accuracy: 85.55\n",
      "Train Epoch: 12 [38400/50000 (85%)]\tLoss: 0.516358, Accuracy: 83.20\n",
      "Train Epoch: 12 [39680/50000 (88%)]\tLoss: 0.474021, Accuracy: 82.81\n",
      "Train Epoch: 12 [40960/50000 (91%)]\tLoss: 0.472666, Accuracy: 84.38\n",
      "Train Epoch: 12 [42240/50000 (94%)]\tLoss: 0.568560, Accuracy: 79.69\n",
      "Train Epoch: 12 [43520/50000 (97%)]\tLoss: 0.343461, Accuracy: 87.50\n",
      "Train Epoch: 12 [35000/50000 (99%)]\tLoss: 0.656735, Accuracy: 80.50\n",
      "\n",
      "Validation set: Average loss: 0.7735, Accuracy: 3784/5000 (75.00%)\n",
      "\n",
      "the time of this epoch:[21.409961938858032 s]\n",
      "Train Epoch: 13 [0/50000 (0%)]\tLoss: 0.539499, Accuracy: 81.25\n",
      "Train Epoch: 13 [1280/50000 (3%)]\tLoss: 0.550409, Accuracy: 82.42\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 13 [2560/50000 (6%)]\tLoss: 0.423779, Accuracy: 84.77\n",
      "Train Epoch: 13 [3840/50000 (9%)]\tLoss: 0.471316, Accuracy: 82.81\n",
      "Train Epoch: 13 [5120/50000 (11%)]\tLoss: 0.317101, Accuracy: 90.62\n",
      "Train Epoch: 13 [6400/50000 (14%)]\tLoss: 0.475564, Accuracy: 84.77\n",
      "Train Epoch: 13 [7680/50000 (17%)]\tLoss: 0.445709, Accuracy: 83.98\n",
      "Train Epoch: 13 [8960/50000 (20%)]\tLoss: 0.506993, Accuracy: 82.42\n",
      "Train Epoch: 13 [10240/50000 (23%)]\tLoss: 0.427775, Accuracy: 83.20\n",
      "Train Epoch: 13 [11520/50000 (26%)]\tLoss: 0.471664, Accuracy: 81.25\n",
      "Train Epoch: 13 [12800/50000 (28%)]\tLoss: 0.505752, Accuracy: 78.12\n",
      "Train Epoch: 13 [14080/50000 (31%)]\tLoss: 0.506504, Accuracy: 83.59\n",
      "Train Epoch: 13 [15360/50000 (34%)]\tLoss: 0.544897, Accuracy: 83.98\n",
      "Train Epoch: 13 [16640/50000 (37%)]\tLoss: 0.437409, Accuracy: 84.77\n",
      "Train Epoch: 13 [17920/50000 (40%)]\tLoss: 0.473282, Accuracy: 84.77\n",
      "Train Epoch: 13 [19200/50000 (43%)]\tLoss: 0.453111, Accuracy: 85.16\n",
      "Train Epoch: 13 [20480/50000 (45%)]\tLoss: 0.535842, Accuracy: 81.25\n",
      "Train Epoch: 13 [21760/50000 (48%)]\tLoss: 0.471439, Accuracy: 83.20\n",
      "Train Epoch: 13 [23040/50000 (51%)]\tLoss: 0.454781, Accuracy: 84.77\n",
      "Train Epoch: 13 [24320/50000 (54%)]\tLoss: 0.522739, Accuracy: 81.64\n",
      "Train Epoch: 13 [25600/50000 (57%)]\tLoss: 0.559816, Accuracy: 80.47\n",
      "Train Epoch: 13 [26880/50000 (60%)]\tLoss: 0.414925, Accuracy: 85.55\n",
      "Train Epoch: 13 [28160/50000 (62%)]\tLoss: 0.487907, Accuracy: 82.42\n",
      "Train Epoch: 13 [29440/50000 (65%)]\tLoss: 0.467152, Accuracy: 83.20\n",
      "Train Epoch: 13 [30720/50000 (68%)]\tLoss: 0.454902, Accuracy: 85.55\n",
      "Train Epoch: 13 [32000/50000 (71%)]\tLoss: 0.559392, Accuracy: 78.91\n",
      "Train Epoch: 13 [33280/50000 (74%)]\tLoss: 0.437637, Accuracy: 84.38\n",
      "Train Epoch: 13 [34560/50000 (77%)]\tLoss: 0.396817, Accuracy: 87.50\n",
      "Train Epoch: 13 [35840/50000 (80%)]\tLoss: 0.417846, Accuracy: 85.55\n",
      "Train Epoch: 13 [37120/50000 (82%)]\tLoss: 0.509938, Accuracy: 83.20\n",
      "Train Epoch: 13 [38400/50000 (85%)]\tLoss: 0.354781, Accuracy: 89.45\n",
      "Train Epoch: 13 [39680/50000 (88%)]\tLoss: 0.466761, Accuracy: 84.38\n",
      "Train Epoch: 13 [40960/50000 (91%)]\tLoss: 0.430618, Accuracy: 84.77\n",
      "Train Epoch: 13 [42240/50000 (94%)]\tLoss: 0.524239, Accuracy: 82.42\n",
      "Train Epoch: 13 [43520/50000 (97%)]\tLoss: 0.404810, Accuracy: 85.94\n",
      "Train Epoch: 13 [35000/50000 (99%)]\tLoss: 0.465058, Accuracy: 85.50\n",
      "\n",
      "Validation set: Average loss: 0.5578, Accuracy: 4055/5000 (81.00%)\n",
      "\n",
      "the time of this epoch:[21.420891523361206 s]\n",
      "Train Epoch: 14 [0/50000 (0%)]\tLoss: 0.479101, Accuracy: 83.20\n",
      "Train Epoch: 14 [1280/50000 (3%)]\tLoss: 0.424892, Accuracy: 85.55\n",
      "Train Epoch: 14 [2560/50000 (6%)]\tLoss: 0.424205, Accuracy: 84.77\n",
      "Train Epoch: 14 [3840/50000 (9%)]\tLoss: 0.484321, Accuracy: 84.38\n",
      "Train Epoch: 14 [5120/50000 (11%)]\tLoss: 0.401800, Accuracy: 85.16\n",
      "Train Epoch: 14 [6400/50000 (14%)]\tLoss: 0.343967, Accuracy: 87.89\n",
      "Train Epoch: 14 [7680/50000 (17%)]\tLoss: 0.494568, Accuracy: 82.81\n",
      "Train Epoch: 14 [8960/50000 (20%)]\tLoss: 0.405555, Accuracy: 85.16\n",
      "Train Epoch: 14 [10240/50000 (23%)]\tLoss: 0.476176, Accuracy: 82.81\n",
      "Train Epoch: 14 [11520/50000 (26%)]\tLoss: 0.478014, Accuracy: 83.98\n",
      "Train Epoch: 14 [12800/50000 (28%)]\tLoss: 0.491201, Accuracy: 82.03\n",
      "Train Epoch: 14 [14080/50000 (31%)]\tLoss: 0.565897, Accuracy: 82.81\n",
      "Train Epoch: 14 [15360/50000 (34%)]\tLoss: 0.522322, Accuracy: 82.42\n",
      "Train Epoch: 14 [16640/50000 (37%)]\tLoss: 0.464967, Accuracy: 80.86\n",
      "Train Epoch: 14 [17920/50000 (40%)]\tLoss: 0.516117, Accuracy: 83.20\n",
      "Train Epoch: 14 [19200/50000 (43%)]\tLoss: 0.329225, Accuracy: 89.45\n",
      "Train Epoch: 14 [20480/50000 (45%)]\tLoss: 0.479110, Accuracy: 82.42\n",
      "Train Epoch: 14 [21760/50000 (48%)]\tLoss: 0.500461, Accuracy: 82.03\n",
      "Train Epoch: 14 [23040/50000 (51%)]\tLoss: 0.464980, Accuracy: 84.38\n",
      "Train Epoch: 14 [24320/50000 (54%)]\tLoss: 0.543359, Accuracy: 84.38\n",
      "Train Epoch: 14 [25600/50000 (57%)]\tLoss: 0.400207, Accuracy: 84.77\n",
      "Train Epoch: 14 [26880/50000 (60%)]\tLoss: 0.421310, Accuracy: 86.72\n",
      "Train Epoch: 14 [28160/50000 (62%)]\tLoss: 0.473339, Accuracy: 83.20\n",
      "Train Epoch: 14 [29440/50000 (65%)]\tLoss: 0.547633, Accuracy: 82.42\n",
      "Train Epoch: 14 [30720/50000 (68%)]\tLoss: 0.527533, Accuracy: 81.25\n",
      "Train Epoch: 14 [32000/50000 (71%)]\tLoss: 0.403837, Accuracy: 85.94\n",
      "Train Epoch: 14 [33280/50000 (74%)]\tLoss: 0.400470, Accuracy: 87.89\n",
      "Train Epoch: 14 [34560/50000 (77%)]\tLoss: 0.385568, Accuracy: 85.94\n",
      "Train Epoch: 14 [35840/50000 (80%)]\tLoss: 0.405963, Accuracy: 84.38\n",
      "Train Epoch: 14 [37120/50000 (82%)]\tLoss: 0.504121, Accuracy: 80.86\n",
      "Train Epoch: 14 [38400/50000 (85%)]\tLoss: 0.566608, Accuracy: 79.69\n",
      "Train Epoch: 14 [39680/50000 (88%)]\tLoss: 0.509676, Accuracy: 80.08\n",
      "Train Epoch: 14 [40960/50000 (91%)]\tLoss: 0.367267, Accuracy: 85.94\n",
      "Train Epoch: 14 [42240/50000 (94%)]\tLoss: 0.490631, Accuracy: 83.98\n",
      "Train Epoch: 14 [43520/50000 (97%)]\tLoss: 0.408478, Accuracy: 85.16\n",
      "Train Epoch: 14 [35000/50000 (99%)]\tLoss: 0.478928, Accuracy: 81.00\n",
      "\n",
      "Validation set: Average loss: 0.5498, Accuracy: 4077/5000 (81.00%)\n",
      "\n",
      "the time of this epoch:[21.423383951187134 s]\n",
      "Train Epoch: 15 [0/50000 (0%)]\tLoss: 0.320613, Accuracy: 89.45\n",
      "Train Epoch: 15 [1280/50000 (3%)]\tLoss: 0.460138, Accuracy: 85.94\n",
      "Train Epoch: 15 [2560/50000 (6%)]\tLoss: 0.435278, Accuracy: 83.98\n",
      "Train Epoch: 15 [3840/50000 (9%)]\tLoss: 0.373557, Accuracy: 86.33\n",
      "Train Epoch: 15 [5120/50000 (11%)]\tLoss: 0.459102, Accuracy: 83.59\n",
      "Train Epoch: 15 [6400/50000 (14%)]\tLoss: 0.395682, Accuracy: 85.55\n",
      "Train Epoch: 15 [7680/50000 (17%)]\tLoss: 0.404361, Accuracy: 84.77\n",
      "Train Epoch: 15 [8960/50000 (20%)]\tLoss: 0.453150, Accuracy: 83.59\n",
      "Train Epoch: 15 [10240/50000 (23%)]\tLoss: 0.320385, Accuracy: 89.45\n",
      "Train Epoch: 15 [11520/50000 (26%)]\tLoss: 0.414945, Accuracy: 84.77\n",
      "Train Epoch: 15 [12800/50000 (28%)]\tLoss: 0.410982, Accuracy: 86.72\n",
      "Train Epoch: 15 [14080/50000 (31%)]\tLoss: 0.408130, Accuracy: 85.16\n",
      "Train Epoch: 15 [15360/50000 (34%)]\tLoss: 0.436673, Accuracy: 84.77\n",
      "Train Epoch: 15 [16640/50000 (37%)]\tLoss: 0.402328, Accuracy: 86.72\n",
      "Train Epoch: 15 [17920/50000 (40%)]\tLoss: 0.449431, Accuracy: 83.98\n",
      "Train Epoch: 15 [19200/50000 (43%)]\tLoss: 0.504722, Accuracy: 84.77\n",
      "Train Epoch: 15 [20480/50000 (45%)]\tLoss: 0.456847, Accuracy: 83.59\n",
      "Train Epoch: 15 [21760/50000 (48%)]\tLoss: 0.531541, Accuracy: 81.64\n",
      "Train Epoch: 15 [23040/50000 (51%)]\tLoss: 0.472858, Accuracy: 83.20\n",
      "Train Epoch: 15 [24320/50000 (54%)]\tLoss: 0.428079, Accuracy: 86.72\n",
      "Train Epoch: 15 [25600/50000 (57%)]\tLoss: 0.420762, Accuracy: 84.77\n",
      "Train Epoch: 15 [26880/50000 (60%)]\tLoss: 0.362548, Accuracy: 85.94\n",
      "Train Epoch: 15 [28160/50000 (62%)]\tLoss: 0.468724, Accuracy: 83.20\n",
      "Train Epoch: 15 [29440/50000 (65%)]\tLoss: 0.393995, Accuracy: 87.11\n",
      "Train Epoch: 15 [30720/50000 (68%)]\tLoss: 0.416630, Accuracy: 87.11\n",
      "Train Epoch: 15 [32000/50000 (71%)]\tLoss: 0.416496, Accuracy: 86.33\n",
      "Train Epoch: 15 [33280/50000 (74%)]\tLoss: 0.362543, Accuracy: 87.89\n",
      "Train Epoch: 15 [34560/50000 (77%)]\tLoss: 0.486123, Accuracy: 82.42\n",
      "Train Epoch: 15 [35840/50000 (80%)]\tLoss: 0.341424, Accuracy: 85.55\n",
      "Train Epoch: 15 [37120/50000 (82%)]\tLoss: 0.485237, Accuracy: 82.42\n",
      "Train Epoch: 15 [38400/50000 (85%)]\tLoss: 0.404662, Accuracy: 86.72\n",
      "Train Epoch: 15 [39680/50000 (88%)]\tLoss: 0.356900, Accuracy: 88.28\n",
      "Train Epoch: 15 [40960/50000 (91%)]\tLoss: 0.347585, Accuracy: 87.89\n",
      "Train Epoch: 15 [42240/50000 (94%)]\tLoss: 0.597126, Accuracy: 80.08\n",
      "Train Epoch: 15 [43520/50000 (97%)]\tLoss: 0.395992, Accuracy: 84.77\n",
      "Train Epoch: 15 [35000/50000 (99%)]\tLoss: 0.416862, Accuracy: 90.00\n",
      "\n",
      "Validation set: Average loss: 0.6208, Accuracy: 4005/5000 (80.00%)\n",
      "\n",
      "the time of this epoch:[21.394246339797974 s]\n",
      "Train Epoch: 16 [0/50000 (0%)]\tLoss: 0.390821, Accuracy: 87.50\n",
      "Train Epoch: 16 [1280/50000 (3%)]\tLoss: 0.422629, Accuracy: 85.55\n",
      "Train Epoch: 16 [2560/50000 (6%)]\tLoss: 0.359999, Accuracy: 86.72\n",
      "Train Epoch: 16 [3840/50000 (9%)]\tLoss: 0.412815, Accuracy: 85.55\n",
      "Train Epoch: 16 [5120/50000 (11%)]\tLoss: 0.443656, Accuracy: 82.81\n",
      "Train Epoch: 16 [6400/50000 (14%)]\tLoss: 0.520726, Accuracy: 82.42\n",
      "Train Epoch: 16 [7680/50000 (17%)]\tLoss: 0.436021, Accuracy: 81.25\n",
      "Train Epoch: 16 [8960/50000 (20%)]\tLoss: 0.418814, Accuracy: 86.33\n",
      "Train Epoch: 16 [10240/50000 (23%)]\tLoss: 0.346543, Accuracy: 88.28\n",
      "Train Epoch: 16 [11520/50000 (26%)]\tLoss: 0.438835, Accuracy: 86.33\n",
      "Train Epoch: 16 [12800/50000 (28%)]\tLoss: 0.393850, Accuracy: 86.72\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 16 [14080/50000 (31%)]\tLoss: 0.442264, Accuracy: 85.94\n",
      "Train Epoch: 16 [15360/50000 (34%)]\tLoss: 0.488379, Accuracy: 86.72\n",
      "Train Epoch: 16 [16640/50000 (37%)]\tLoss: 0.346645, Accuracy: 87.50\n",
      "Train Epoch: 16 [17920/50000 (40%)]\tLoss: 0.382793, Accuracy: 87.11\n",
      "Train Epoch: 16 [19200/50000 (43%)]\tLoss: 0.417352, Accuracy: 86.33\n",
      "Train Epoch: 16 [20480/50000 (45%)]\tLoss: 0.418866, Accuracy: 85.16\n",
      "Train Epoch: 16 [21760/50000 (48%)]\tLoss: 0.554143, Accuracy: 81.25\n",
      "Train Epoch: 16 [23040/50000 (51%)]\tLoss: 0.607496, Accuracy: 80.86\n",
      "Train Epoch: 16 [24320/50000 (54%)]\tLoss: 0.405321, Accuracy: 85.94\n",
      "Train Epoch: 16 [25600/50000 (57%)]\tLoss: 0.415325, Accuracy: 84.77\n",
      "Train Epoch: 16 [26880/50000 (60%)]\tLoss: 0.426344, Accuracy: 85.16\n",
      "Train Epoch: 16 [28160/50000 (62%)]\tLoss: 0.434556, Accuracy: 85.16\n",
      "Train Epoch: 16 [29440/50000 (65%)]\tLoss: 0.499840, Accuracy: 82.03\n",
      "Train Epoch: 16 [30720/50000 (68%)]\tLoss: 0.575733, Accuracy: 80.08\n",
      "Train Epoch: 16 [32000/50000 (71%)]\tLoss: 0.352028, Accuracy: 85.55\n",
      "Train Epoch: 16 [33280/50000 (74%)]\tLoss: 0.441847, Accuracy: 83.98\n",
      "Train Epoch: 16 [34560/50000 (77%)]\tLoss: 0.373279, Accuracy: 85.94\n",
      "Train Epoch: 16 [35840/50000 (80%)]\tLoss: 0.416798, Accuracy: 85.16\n",
      "Train Epoch: 16 [37120/50000 (82%)]\tLoss: 0.295218, Accuracy: 89.45\n",
      "Train Epoch: 16 [38400/50000 (85%)]\tLoss: 0.405055, Accuracy: 87.89\n",
      "Train Epoch: 16 [39680/50000 (88%)]\tLoss: 0.421916, Accuracy: 86.72\n",
      "Train Epoch: 16 [40960/50000 (91%)]\tLoss: 0.533286, Accuracy: 83.59\n",
      "Train Epoch: 16 [42240/50000 (94%)]\tLoss: 0.361913, Accuracy: 86.33\n",
      "Train Epoch: 16 [43520/50000 (97%)]\tLoss: 0.416484, Accuracy: 87.50\n",
      "Train Epoch: 16 [35000/50000 (99%)]\tLoss: 0.419351, Accuracy: 85.50\n",
      "\n",
      "Validation set: Average loss: 0.5486, Accuracy: 4066/5000 (81.00%)\n",
      "\n",
      "the time of this epoch:[21.466911792755127 s]\n",
      "Train Epoch: 17 [0/50000 (0%)]\tLoss: 0.364785, Accuracy: 85.94\n",
      "Train Epoch: 17 [1280/50000 (3%)]\tLoss: 0.397157, Accuracy: 86.33\n",
      "Train Epoch: 17 [2560/50000 (6%)]\tLoss: 0.397887, Accuracy: 85.16\n",
      "Train Epoch: 17 [3840/50000 (9%)]\tLoss: 0.404899, Accuracy: 87.50\n",
      "Train Epoch: 17 [5120/50000 (11%)]\tLoss: 0.331283, Accuracy: 89.84\n",
      "Train Epoch: 17 [6400/50000 (14%)]\tLoss: 0.355242, Accuracy: 85.55\n",
      "Train Epoch: 17 [7680/50000 (17%)]\tLoss: 0.430243, Accuracy: 84.38\n",
      "Train Epoch: 17 [8960/50000 (20%)]\tLoss: 0.383861, Accuracy: 86.72\n",
      "Train Epoch: 17 [10240/50000 (23%)]\tLoss: 0.410224, Accuracy: 87.11\n",
      "Train Epoch: 17 [11520/50000 (26%)]\tLoss: 0.425522, Accuracy: 86.72\n",
      "Train Epoch: 17 [12800/50000 (28%)]\tLoss: 0.580895, Accuracy: 83.59\n",
      "Train Epoch: 17 [14080/50000 (31%)]\tLoss: 0.434645, Accuracy: 83.59\n",
      "Train Epoch: 17 [15360/50000 (34%)]\tLoss: 0.469508, Accuracy: 85.94\n",
      "Train Epoch: 17 [16640/50000 (37%)]\tLoss: 0.381921, Accuracy: 87.11\n",
      "Train Epoch: 17 [17920/50000 (40%)]\tLoss: 0.309039, Accuracy: 89.06\n",
      "Train Epoch: 17 [19200/50000 (43%)]\tLoss: 0.367467, Accuracy: 86.33\n",
      "Train Epoch: 17 [20480/50000 (45%)]\tLoss: 0.445854, Accuracy: 83.20\n",
      "Train Epoch: 17 [21760/50000 (48%)]\tLoss: 0.439555, Accuracy: 84.38\n",
      "Train Epoch: 17 [23040/50000 (51%)]\tLoss: 0.409741, Accuracy: 86.33\n",
      "Train Epoch: 17 [24320/50000 (54%)]\tLoss: 0.349431, Accuracy: 87.89\n",
      "Train Epoch: 17 [25600/50000 (57%)]\tLoss: 0.334741, Accuracy: 87.50\n",
      "Train Epoch: 17 [26880/50000 (60%)]\tLoss: 0.428771, Accuracy: 87.50\n",
      "Train Epoch: 17 [28160/50000 (62%)]\tLoss: 0.556106, Accuracy: 85.16\n",
      "Train Epoch: 17 [29440/50000 (65%)]\tLoss: 0.437718, Accuracy: 85.16\n",
      "Train Epoch: 17 [30720/50000 (68%)]\tLoss: 0.378778, Accuracy: 87.50\n",
      "Train Epoch: 17 [32000/50000 (71%)]\tLoss: 0.397431, Accuracy: 87.11\n",
      "Train Epoch: 17 [33280/50000 (74%)]\tLoss: 0.399936, Accuracy: 84.77\n",
      "Train Epoch: 17 [34560/50000 (77%)]\tLoss: 0.374026, Accuracy: 87.50\n",
      "Train Epoch: 17 [35840/50000 (80%)]\tLoss: 0.326051, Accuracy: 89.45\n",
      "Train Epoch: 17 [37120/50000 (82%)]\tLoss: 0.418527, Accuracy: 86.72\n",
      "Train Epoch: 17 [38400/50000 (85%)]\tLoss: 0.416285, Accuracy: 86.72\n",
      "Train Epoch: 17 [39680/50000 (88%)]\tLoss: 0.359783, Accuracy: 86.72\n",
      "Train Epoch: 17 [40960/50000 (91%)]\tLoss: 0.524308, Accuracy: 79.69\n",
      "Train Epoch: 17 [42240/50000 (94%)]\tLoss: 0.337179, Accuracy: 88.67\n",
      "Train Epoch: 17 [43520/50000 (97%)]\tLoss: 0.519321, Accuracy: 80.47\n",
      "Train Epoch: 17 [35000/50000 (99%)]\tLoss: 0.536773, Accuracy: 79.50\n",
      "\n",
      "Validation set: Average loss: 0.5109, Accuracy: 4143/5000 (82.00%)\n",
      "\n",
      "the time of this epoch:[21.471716165542603 s]\n",
      "Train Epoch: 18 [0/50000 (0%)]\tLoss: 0.387443, Accuracy: 86.72\n",
      "Train Epoch: 18 [1280/50000 (3%)]\tLoss: 0.341105, Accuracy: 85.16\n",
      "Train Epoch: 18 [2560/50000 (6%)]\tLoss: 0.323874, Accuracy: 88.67\n",
      "Train Epoch: 18 [3840/50000 (9%)]\tLoss: 0.400539, Accuracy: 86.33\n",
      "Train Epoch: 18 [5120/50000 (11%)]\tLoss: 0.361400, Accuracy: 89.06\n",
      "Train Epoch: 18 [6400/50000 (14%)]\tLoss: 0.404247, Accuracy: 84.38\n",
      "Train Epoch: 18 [7680/50000 (17%)]\tLoss: 0.288266, Accuracy: 91.80\n",
      "Train Epoch: 18 [8960/50000 (20%)]\tLoss: 0.322303, Accuracy: 88.28\n",
      "Train Epoch: 18 [10240/50000 (23%)]\tLoss: 0.354537, Accuracy: 87.89\n",
      "Train Epoch: 18 [11520/50000 (26%)]\tLoss: 0.474869, Accuracy: 85.16\n",
      "Train Epoch: 18 [12800/50000 (28%)]\tLoss: 0.356548, Accuracy: 88.28\n",
      "Train Epoch: 18 [14080/50000 (31%)]\tLoss: 0.384895, Accuracy: 89.84\n",
      "Train Epoch: 18 [15360/50000 (34%)]\tLoss: 0.403579, Accuracy: 87.89\n",
      "Train Epoch: 18 [16640/50000 (37%)]\tLoss: 0.496296, Accuracy: 80.47\n",
      "Train Epoch: 18 [17920/50000 (40%)]\tLoss: 0.469085, Accuracy: 87.50\n",
      "Train Epoch: 18 [19200/50000 (43%)]\tLoss: 0.304689, Accuracy: 90.23\n",
      "Train Epoch: 18 [20480/50000 (45%)]\tLoss: 0.495439, Accuracy: 84.38\n",
      "Train Epoch: 18 [21760/50000 (48%)]\tLoss: 0.373185, Accuracy: 87.11\n",
      "Train Epoch: 18 [23040/50000 (51%)]\tLoss: 0.339941, Accuracy: 86.72\n",
      "Train Epoch: 18 [24320/50000 (54%)]\tLoss: 0.425143, Accuracy: 84.77\n",
      "Train Epoch: 18 [25600/50000 (57%)]\tLoss: 0.296150, Accuracy: 89.45\n",
      "Train Epoch: 18 [26880/50000 (60%)]\tLoss: 0.495855, Accuracy: 85.16\n",
      "Train Epoch: 18 [28160/50000 (62%)]\tLoss: 0.382837, Accuracy: 86.33\n",
      "Train Epoch: 18 [29440/50000 (65%)]\tLoss: 0.333197, Accuracy: 88.67\n",
      "Train Epoch: 18 [30720/50000 (68%)]\tLoss: 0.339388, Accuracy: 87.89\n",
      "Train Epoch: 18 [32000/50000 (71%)]\tLoss: 0.372995, Accuracy: 86.72\n",
      "Train Epoch: 18 [33280/50000 (74%)]\tLoss: 0.370483, Accuracy: 87.50\n",
      "Train Epoch: 18 [34560/50000 (77%)]\tLoss: 0.437422, Accuracy: 84.77\n",
      "Train Epoch: 18 [35840/50000 (80%)]\tLoss: 0.557250, Accuracy: 80.08\n",
      "Train Epoch: 18 [37120/50000 (82%)]\tLoss: 0.350450, Accuracy: 89.45\n",
      "Train Epoch: 18 [38400/50000 (85%)]\tLoss: 0.442403, Accuracy: 85.16\n",
      "Train Epoch: 18 [39680/50000 (88%)]\tLoss: 0.395560, Accuracy: 84.38\n",
      "Train Epoch: 18 [40960/50000 (91%)]\tLoss: 0.429399, Accuracy: 84.77\n",
      "Train Epoch: 18 [42240/50000 (94%)]\tLoss: 0.554983, Accuracy: 83.59\n",
      "Train Epoch: 18 [43520/50000 (97%)]\tLoss: 0.546071, Accuracy: 82.03\n",
      "Train Epoch: 18 [35000/50000 (99%)]\tLoss: 0.405996, Accuracy: 85.00\n",
      "\n",
      "Validation set: Average loss: 0.5976, Accuracy: 4054/5000 (81.00%)\n",
      "\n",
      "the time of this epoch:[21.470532178878784 s]\n",
      "Train Epoch: 19 [0/50000 (0%)]\tLoss: 0.366750, Accuracy: 86.72\n",
      "Train Epoch: 19 [1280/50000 (3%)]\tLoss: 0.320147, Accuracy: 90.23\n",
      "Train Epoch: 19 [2560/50000 (6%)]\tLoss: 0.443083, Accuracy: 84.77\n",
      "Train Epoch: 19 [3840/50000 (9%)]\tLoss: 0.397248, Accuracy: 86.72\n",
      "Train Epoch: 19 [5120/50000 (11%)]\tLoss: 0.355158, Accuracy: 85.55\n",
      "Train Epoch: 19 [6400/50000 (14%)]\tLoss: 0.337048, Accuracy: 89.45\n",
      "Train Epoch: 19 [7680/50000 (17%)]\tLoss: 0.338661, Accuracy: 87.50\n",
      "Train Epoch: 19 [8960/50000 (20%)]\tLoss: 0.442998, Accuracy: 83.20\n",
      "Train Epoch: 19 [10240/50000 (23%)]\tLoss: 0.446307, Accuracy: 83.98\n",
      "Train Epoch: 19 [11520/50000 (26%)]\tLoss: 0.450764, Accuracy: 84.38\n",
      "Train Epoch: 19 [12800/50000 (28%)]\tLoss: 0.347246, Accuracy: 88.28\n",
      "Train Epoch: 19 [14080/50000 (31%)]\tLoss: 0.325760, Accuracy: 88.28\n",
      "Train Epoch: 19 [15360/50000 (34%)]\tLoss: 0.505035, Accuracy: 81.64\n",
      "Train Epoch: 19 [16640/50000 (37%)]\tLoss: 0.413884, Accuracy: 86.72\n",
      "Train Epoch: 19 [17920/50000 (40%)]\tLoss: 0.403922, Accuracy: 85.94\n",
      "Train Epoch: 19 [19200/50000 (43%)]\tLoss: 0.468707, Accuracy: 83.20\n",
      "Train Epoch: 19 [20480/50000 (45%)]\tLoss: 0.368470, Accuracy: 87.89\n",
      "Train Epoch: 19 [21760/50000 (48%)]\tLoss: 0.422607, Accuracy: 84.77\n",
      "Train Epoch: 19 [23040/50000 (51%)]\tLoss: 0.383451, Accuracy: 87.11\n",
      "Train Epoch: 19 [24320/50000 (54%)]\tLoss: 0.386874, Accuracy: 86.33\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 19 [25600/50000 (57%)]\tLoss: 0.346747, Accuracy: 88.28\n",
      "Train Epoch: 19 [26880/50000 (60%)]\tLoss: 0.341145, Accuracy: 88.28\n",
      "Train Epoch: 19 [28160/50000 (62%)]\tLoss: 0.441644, Accuracy: 83.98\n",
      "Train Epoch: 19 [29440/50000 (65%)]\tLoss: 0.402923, Accuracy: 87.89\n",
      "Train Epoch: 19 [30720/50000 (68%)]\tLoss: 0.370942, Accuracy: 85.94\n",
      "Train Epoch: 19 [32000/50000 (71%)]\tLoss: 0.368174, Accuracy: 86.33\n",
      "Train Epoch: 19 [33280/50000 (74%)]\tLoss: 0.371050, Accuracy: 85.16\n",
      "Train Epoch: 19 [34560/50000 (77%)]\tLoss: 0.354309, Accuracy: 87.50\n",
      "Train Epoch: 19 [35840/50000 (80%)]\tLoss: 0.423765, Accuracy: 82.81\n",
      "Train Epoch: 19 [37120/50000 (82%)]\tLoss: 0.411034, Accuracy: 86.33\n",
      "Train Epoch: 19 [38400/50000 (85%)]\tLoss: 0.395071, Accuracy: 85.16\n",
      "Train Epoch: 19 [39680/50000 (88%)]\tLoss: 0.351977, Accuracy: 87.89\n",
      "Train Epoch: 19 [40960/50000 (91%)]\tLoss: 0.412741, Accuracy: 85.16\n",
      "Train Epoch: 19 [42240/50000 (94%)]\tLoss: 0.578038, Accuracy: 81.64\n",
      "Train Epoch: 19 [43520/50000 (97%)]\tLoss: 0.273718, Accuracy: 89.06\n",
      "Train Epoch: 19 [35000/50000 (99%)]\tLoss: 0.364596, Accuracy: 87.00\n",
      "\n",
      "Validation set: Average loss: 0.5729, Accuracy: 4095/5000 (81.00%)\n",
      "\n",
      "the time of this epoch:[21.480185985565186 s]\n",
      "Train Epoch: 20 [0/50000 (0%)]\tLoss: 0.339619, Accuracy: 89.06\n",
      "Train Epoch: 20 [1280/50000 (3%)]\tLoss: 0.390545, Accuracy: 87.50\n",
      "Train Epoch: 20 [2560/50000 (6%)]\tLoss: 0.423481, Accuracy: 85.94\n",
      "Train Epoch: 20 [3840/50000 (9%)]\tLoss: 0.405789, Accuracy: 86.72\n",
      "Train Epoch: 20 [5120/50000 (11%)]\tLoss: 0.321741, Accuracy: 90.62\n",
      "Train Epoch: 20 [6400/50000 (14%)]\tLoss: 0.273285, Accuracy: 89.84\n",
      "Train Epoch: 20 [7680/50000 (17%)]\tLoss: 0.334638, Accuracy: 89.06\n",
      "Train Epoch: 20 [8960/50000 (20%)]\tLoss: 0.329058, Accuracy: 87.89\n",
      "Train Epoch: 20 [10240/50000 (23%)]\tLoss: 0.404647, Accuracy: 88.28\n",
      "Train Epoch: 20 [11520/50000 (26%)]\tLoss: 0.325788, Accuracy: 87.50\n",
      "Train Epoch: 20 [12800/50000 (28%)]\tLoss: 0.355563, Accuracy: 87.89\n",
      "Train Epoch: 20 [14080/50000 (31%)]\tLoss: 0.327206, Accuracy: 87.89\n",
      "Train Epoch: 20 [15360/50000 (34%)]\tLoss: 0.391963, Accuracy: 84.77\n",
      "Train Epoch: 20 [16640/50000 (37%)]\tLoss: 0.388321, Accuracy: 87.89\n",
      "Train Epoch: 20 [17920/50000 (40%)]\tLoss: 0.421325, Accuracy: 84.38\n",
      "Train Epoch: 20 [19200/50000 (43%)]\tLoss: 0.343511, Accuracy: 87.89\n",
      "Train Epoch: 20 [20480/50000 (45%)]\tLoss: 0.346844, Accuracy: 89.45\n",
      "Train Epoch: 20 [21760/50000 (48%)]\tLoss: 0.318131, Accuracy: 90.23\n",
      "Train Epoch: 20 [23040/50000 (51%)]\tLoss: 0.323881, Accuracy: 87.89\n",
      "Train Epoch: 20 [24320/50000 (54%)]\tLoss: 0.386500, Accuracy: 87.50\n",
      "Train Epoch: 20 [25600/50000 (57%)]\tLoss: 0.392051, Accuracy: 88.28\n",
      "Train Epoch: 20 [26880/50000 (60%)]\tLoss: 0.382632, Accuracy: 85.55\n",
      "Train Epoch: 20 [28160/50000 (62%)]\tLoss: 0.466734, Accuracy: 82.03\n",
      "Train Epoch: 20 [29440/50000 (65%)]\tLoss: 0.315473, Accuracy: 90.62\n",
      "Train Epoch: 20 [30720/50000 (68%)]\tLoss: 0.430142, Accuracy: 85.94\n",
      "Train Epoch: 20 [32000/50000 (71%)]\tLoss: 0.386357, Accuracy: 87.50\n",
      "Train Epoch: 20 [33280/50000 (74%)]\tLoss: 0.387498, Accuracy: 85.16\n",
      "Train Epoch: 20 [34560/50000 (77%)]\tLoss: 0.368477, Accuracy: 86.33\n",
      "Train Epoch: 20 [35840/50000 (80%)]\tLoss: 0.462810, Accuracy: 85.55\n",
      "Train Epoch: 20 [37120/50000 (82%)]\tLoss: 0.402462, Accuracy: 84.77\n",
      "Train Epoch: 20 [38400/50000 (85%)]\tLoss: 0.358546, Accuracy: 87.50\n",
      "Train Epoch: 20 [39680/50000 (88%)]\tLoss: 0.446391, Accuracy: 83.20\n",
      "Train Epoch: 20 [40960/50000 (91%)]\tLoss: 0.307589, Accuracy: 91.02\n",
      "Train Epoch: 20 [42240/50000 (94%)]\tLoss: 0.421000, Accuracy: 86.72\n",
      "Train Epoch: 20 [43520/50000 (97%)]\tLoss: 0.381791, Accuracy: 87.11\n",
      "Train Epoch: 20 [35000/50000 (99%)]\tLoss: 0.381630, Accuracy: 85.00\n",
      "\n",
      "Validation set: Average loss: 0.5012, Accuracy: 4177/5000 (83.00%)\n",
      "\n",
      "the time of this epoch:[21.480892419815063 s]\n",
      "Train Epoch: 21 [0/50000 (0%)]\tLoss: 0.323087, Accuracy: 89.45\n",
      "Train Epoch: 21 [1280/50000 (3%)]\tLoss: 0.415047, Accuracy: 83.20\n",
      "Train Epoch: 21 [2560/50000 (6%)]\tLoss: 0.295295, Accuracy: 89.84\n",
      "Train Epoch: 21 [3840/50000 (9%)]\tLoss: 0.332842, Accuracy: 87.11\n",
      "Train Epoch: 21 [5120/50000 (11%)]\tLoss: 0.336314, Accuracy: 88.67\n",
      "Train Epoch: 21 [6400/50000 (14%)]\tLoss: 0.339709, Accuracy: 87.11\n",
      "Train Epoch: 21 [7680/50000 (17%)]\tLoss: 0.286932, Accuracy: 89.06\n",
      "Train Epoch: 21 [8960/50000 (20%)]\tLoss: 0.318541, Accuracy: 88.28\n",
      "Train Epoch: 21 [10240/50000 (23%)]\tLoss: 0.295852, Accuracy: 89.45\n",
      "Train Epoch: 21 [11520/50000 (26%)]\tLoss: 0.296243, Accuracy: 90.23\n",
      "Train Epoch: 21 [12800/50000 (28%)]\tLoss: 0.285027, Accuracy: 89.84\n",
      "Train Epoch: 21 [14080/50000 (31%)]\tLoss: 0.231699, Accuracy: 92.19\n",
      "Train Epoch: 21 [15360/50000 (34%)]\tLoss: 0.263408, Accuracy: 91.41\n",
      "Train Epoch: 21 [16640/50000 (37%)]\tLoss: 0.273575, Accuracy: 92.19\n",
      "Train Epoch: 21 [17920/50000 (40%)]\tLoss: 0.332286, Accuracy: 87.50\n",
      "Train Epoch: 21 [19200/50000 (43%)]\tLoss: 0.339480, Accuracy: 88.28\n",
      "Train Epoch: 21 [20480/50000 (45%)]\tLoss: 0.269994, Accuracy: 89.06\n",
      "Train Epoch: 21 [21760/50000 (48%)]\tLoss: 0.354560, Accuracy: 86.33\n",
      "Train Epoch: 21 [23040/50000 (51%)]\tLoss: 0.282355, Accuracy: 90.62\n",
      "Train Epoch: 21 [24320/50000 (54%)]\tLoss: 0.232224, Accuracy: 92.58\n",
      "Train Epoch: 21 [25600/50000 (57%)]\tLoss: 0.307161, Accuracy: 88.67\n",
      "Train Epoch: 21 [26880/50000 (60%)]\tLoss: 0.296846, Accuracy: 90.23\n",
      "Train Epoch: 21 [28160/50000 (62%)]\tLoss: 0.287923, Accuracy: 88.67\n",
      "Train Epoch: 21 [29440/50000 (65%)]\tLoss: 0.351673, Accuracy: 87.11\n",
      "Train Epoch: 21 [30720/50000 (68%)]\tLoss: 0.261792, Accuracy: 92.19\n",
      "Train Epoch: 21 [32000/50000 (71%)]\tLoss: 0.318488, Accuracy: 89.45\n",
      "Train Epoch: 21 [33280/50000 (74%)]\tLoss: 0.321412, Accuracy: 88.28\n",
      "Train Epoch: 21 [34560/50000 (77%)]\tLoss: 0.268006, Accuracy: 92.58\n",
      "Train Epoch: 21 [35840/50000 (80%)]\tLoss: 0.264872, Accuracy: 89.84\n",
      "Train Epoch: 21 [37120/50000 (82%)]\tLoss: 0.386034, Accuracy: 85.94\n",
      "Train Epoch: 21 [38400/50000 (85%)]\tLoss: 0.267511, Accuracy: 89.84\n",
      "Train Epoch: 21 [39680/50000 (88%)]\tLoss: 0.250148, Accuracy: 91.41\n",
      "Train Epoch: 21 [40960/50000 (91%)]\tLoss: 0.313918, Accuracy: 91.02\n",
      "Train Epoch: 21 [42240/50000 (94%)]\tLoss: 0.239037, Accuracy: 91.41\n",
      "Train Epoch: 21 [43520/50000 (97%)]\tLoss: 0.323379, Accuracy: 89.45\n",
      "Train Epoch: 21 [35000/50000 (99%)]\tLoss: 0.244795, Accuracy: 91.50\n",
      "\n",
      "Validation set: Average loss: 0.4003, Accuracy: 4356/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.423673152923584 s]\n",
      "Train Epoch: 22 [0/50000 (0%)]\tLoss: 0.302842, Accuracy: 89.45\n",
      "Train Epoch: 22 [1280/50000 (3%)]\tLoss: 0.199820, Accuracy: 92.97\n",
      "Train Epoch: 22 [2560/50000 (6%)]\tLoss: 0.205954, Accuracy: 93.36\n",
      "Train Epoch: 22 [3840/50000 (9%)]\tLoss: 0.355847, Accuracy: 85.94\n",
      "Train Epoch: 22 [5120/50000 (11%)]\tLoss: 0.340019, Accuracy: 87.11\n",
      "Train Epoch: 22 [6400/50000 (14%)]\tLoss: 0.285843, Accuracy: 90.62\n",
      "Train Epoch: 22 [7680/50000 (17%)]\tLoss: 0.290223, Accuracy: 90.62\n",
      "Train Epoch: 22 [8960/50000 (20%)]\tLoss: 0.225698, Accuracy: 92.19\n",
      "Train Epoch: 22 [10240/50000 (23%)]\tLoss: 0.237570, Accuracy: 91.41\n",
      "Train Epoch: 22 [11520/50000 (26%)]\tLoss: 0.251252, Accuracy: 92.19\n",
      "Train Epoch: 22 [12800/50000 (28%)]\tLoss: 0.284327, Accuracy: 89.84\n",
      "Train Epoch: 22 [14080/50000 (31%)]\tLoss: 0.277911, Accuracy: 90.62\n",
      "Train Epoch: 22 [15360/50000 (34%)]\tLoss: 0.335048, Accuracy: 87.11\n",
      "Train Epoch: 22 [16640/50000 (37%)]\tLoss: 0.313814, Accuracy: 89.45\n",
      "Train Epoch: 22 [17920/50000 (40%)]\tLoss: 0.292008, Accuracy: 90.23\n",
      "Train Epoch: 22 [19200/50000 (43%)]\tLoss: 0.257727, Accuracy: 91.80\n",
      "Train Epoch: 22 [20480/50000 (45%)]\tLoss: 0.278191, Accuracy: 92.58\n",
      "Train Epoch: 22 [21760/50000 (48%)]\tLoss: 0.325148, Accuracy: 89.84\n",
      "Train Epoch: 22 [23040/50000 (51%)]\tLoss: 0.305633, Accuracy: 89.45\n",
      "Train Epoch: 22 [24320/50000 (54%)]\tLoss: 0.324733, Accuracy: 90.23\n",
      "Train Epoch: 22 [25600/50000 (57%)]\tLoss: 0.325362, Accuracy: 89.45\n",
      "Train Epoch: 22 [26880/50000 (60%)]\tLoss: 0.309094, Accuracy: 89.06\n",
      "Train Epoch: 22 [28160/50000 (62%)]\tLoss: 0.292198, Accuracy: 89.06\n",
      "Train Epoch: 22 [29440/50000 (65%)]\tLoss: 0.292081, Accuracy: 90.23\n",
      "Train Epoch: 22 [30720/50000 (68%)]\tLoss: 0.254045, Accuracy: 91.41\n",
      "Train Epoch: 22 [32000/50000 (71%)]\tLoss: 0.352359, Accuracy: 87.89\n",
      "Train Epoch: 22 [33280/50000 (74%)]\tLoss: 0.213762, Accuracy: 92.58\n",
      "Train Epoch: 22 [34560/50000 (77%)]\tLoss: 0.259765, Accuracy: 91.02\n",
      "Train Epoch: 22 [35840/50000 (80%)]\tLoss: 0.269553, Accuracy: 93.36\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 22 [37120/50000 (82%)]\tLoss: 0.290400, Accuracy: 90.62\n",
      "Train Epoch: 22 [38400/50000 (85%)]\tLoss: 0.240611, Accuracy: 91.41\n",
      "Train Epoch: 22 [39680/50000 (88%)]\tLoss: 0.319886, Accuracy: 88.67\n",
      "Train Epoch: 22 [40960/50000 (91%)]\tLoss: 0.326107, Accuracy: 90.23\n",
      "Train Epoch: 22 [42240/50000 (94%)]\tLoss: 0.282395, Accuracy: 89.06\n",
      "Train Epoch: 22 [43520/50000 (97%)]\tLoss: 0.290910, Accuracy: 87.50\n",
      "Train Epoch: 22 [35000/50000 (99%)]\tLoss: 0.353229, Accuracy: 90.00\n",
      "\n",
      "Validation set: Average loss: 0.3865, Accuracy: 4348/5000 (86.00%)\n",
      "\n",
      "the time of this epoch:[21.41311240196228 s]\n",
      "Train Epoch: 23 [0/50000 (0%)]\tLoss: 0.234393, Accuracy: 93.75\n",
      "Train Epoch: 23 [1280/50000 (3%)]\tLoss: 0.243730, Accuracy: 91.80\n",
      "Train Epoch: 23 [2560/50000 (6%)]\tLoss: 0.244459, Accuracy: 91.02\n",
      "Train Epoch: 23 [3840/50000 (9%)]\tLoss: 0.233951, Accuracy: 93.75\n",
      "Train Epoch: 23 [5120/50000 (11%)]\tLoss: 0.226083, Accuracy: 92.97\n",
      "Train Epoch: 23 [6400/50000 (14%)]\tLoss: 0.205470, Accuracy: 93.75\n",
      "Train Epoch: 23 [7680/50000 (17%)]\tLoss: 0.270550, Accuracy: 90.23\n",
      "Train Epoch: 23 [8960/50000 (20%)]\tLoss: 0.247966, Accuracy: 91.41\n",
      "Train Epoch: 23 [10240/50000 (23%)]\tLoss: 0.333544, Accuracy: 88.28\n",
      "Train Epoch: 23 [11520/50000 (26%)]\tLoss: 0.224515, Accuracy: 92.97\n",
      "Train Epoch: 23 [12800/50000 (28%)]\tLoss: 0.225645, Accuracy: 91.02\n",
      "Train Epoch: 23 [14080/50000 (31%)]\tLoss: 0.266623, Accuracy: 91.02\n",
      "Train Epoch: 23 [15360/50000 (34%)]\tLoss: 0.221149, Accuracy: 93.75\n",
      "Train Epoch: 23 [16640/50000 (37%)]\tLoss: 0.317530, Accuracy: 91.02\n",
      "Train Epoch: 23 [17920/50000 (40%)]\tLoss: 0.280590, Accuracy: 91.41\n",
      "Train Epoch: 23 [19200/50000 (43%)]\tLoss: 0.195477, Accuracy: 94.14\n",
      "Train Epoch: 23 [20480/50000 (45%)]\tLoss: 0.271444, Accuracy: 90.23\n",
      "Train Epoch: 23 [21760/50000 (48%)]\tLoss: 0.194383, Accuracy: 94.53\n",
      "Train Epoch: 23 [23040/50000 (51%)]\tLoss: 0.238390, Accuracy: 89.06\n",
      "Train Epoch: 23 [24320/50000 (54%)]\tLoss: 0.366080, Accuracy: 86.33\n",
      "Train Epoch: 23 [25600/50000 (57%)]\tLoss: 0.264720, Accuracy: 90.23\n",
      "Train Epoch: 23 [26880/50000 (60%)]\tLoss: 0.263670, Accuracy: 90.23\n",
      "Train Epoch: 23 [28160/50000 (62%)]\tLoss: 0.302310, Accuracy: 90.23\n",
      "Train Epoch: 23 [29440/50000 (65%)]\tLoss: 0.251456, Accuracy: 90.62\n",
      "Train Epoch: 23 [30720/50000 (68%)]\tLoss: 0.385605, Accuracy: 86.33\n",
      "Train Epoch: 23 [32000/50000 (71%)]\tLoss: 0.390480, Accuracy: 84.77\n",
      "Train Epoch: 23 [33280/50000 (74%)]\tLoss: 0.276533, Accuracy: 92.19\n",
      "Train Epoch: 23 [34560/50000 (77%)]\tLoss: 0.352943, Accuracy: 88.28\n",
      "Train Epoch: 23 [35840/50000 (80%)]\tLoss: 0.308732, Accuracy: 89.84\n",
      "Train Epoch: 23 [37120/50000 (82%)]\tLoss: 0.241991, Accuracy: 91.41\n",
      "Train Epoch: 23 [38400/50000 (85%)]\tLoss: 0.210863, Accuracy: 91.80\n",
      "Train Epoch: 23 [39680/50000 (88%)]\tLoss: 0.289108, Accuracy: 88.67\n",
      "Train Epoch: 23 [40960/50000 (91%)]\tLoss: 0.251662, Accuracy: 91.80\n",
      "Train Epoch: 23 [42240/50000 (94%)]\tLoss: 0.223498, Accuracy: 91.41\n",
      "Train Epoch: 23 [43520/50000 (97%)]\tLoss: 0.262384, Accuracy: 90.23\n",
      "Train Epoch: 23 [35000/50000 (99%)]\tLoss: 0.349395, Accuracy: 89.00\n",
      "\n",
      "Validation set: Average loss: 0.3983, Accuracy: 4369/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.460394620895386 s]\n",
      "Train Epoch: 24 [0/50000 (0%)]\tLoss: 0.267573, Accuracy: 90.62\n",
      "Train Epoch: 24 [1280/50000 (3%)]\tLoss: 0.252687, Accuracy: 92.19\n",
      "Train Epoch: 24 [2560/50000 (6%)]\tLoss: 0.260966, Accuracy: 90.62\n",
      "Train Epoch: 24 [3840/50000 (9%)]\tLoss: 0.281869, Accuracy: 87.89\n",
      "Train Epoch: 24 [5120/50000 (11%)]\tLoss: 0.186385, Accuracy: 93.75\n",
      "Train Epoch: 24 [6400/50000 (14%)]\tLoss: 0.242670, Accuracy: 92.58\n",
      "Train Epoch: 24 [7680/50000 (17%)]\tLoss: 0.209167, Accuracy: 92.58\n",
      "Train Epoch: 24 [8960/50000 (20%)]\tLoss: 0.339984, Accuracy: 88.28\n",
      "Train Epoch: 24 [10240/50000 (23%)]\tLoss: 0.238742, Accuracy: 93.36\n",
      "Train Epoch: 24 [11520/50000 (26%)]\tLoss: 0.281460, Accuracy: 89.06\n",
      "Train Epoch: 24 [12800/50000 (28%)]\tLoss: 0.221997, Accuracy: 92.97\n",
      "Train Epoch: 24 [14080/50000 (31%)]\tLoss: 0.236960, Accuracy: 90.62\n",
      "Train Epoch: 24 [15360/50000 (34%)]\tLoss: 0.253754, Accuracy: 90.62\n",
      "Train Epoch: 24 [16640/50000 (37%)]\tLoss: 0.320688, Accuracy: 91.41\n",
      "Train Epoch: 24 [17920/50000 (40%)]\tLoss: 0.220235, Accuracy: 92.58\n",
      "Train Epoch: 24 [19200/50000 (43%)]\tLoss: 0.189544, Accuracy: 94.92\n",
      "Train Epoch: 24 [20480/50000 (45%)]\tLoss: 0.286531, Accuracy: 90.23\n",
      "Train Epoch: 24 [21760/50000 (48%)]\tLoss: 0.273112, Accuracy: 91.41\n",
      "Train Epoch: 24 [23040/50000 (51%)]\tLoss: 0.242513, Accuracy: 92.97\n",
      "Train Epoch: 24 [24320/50000 (54%)]\tLoss: 0.306956, Accuracy: 91.80\n",
      "Train Epoch: 24 [25600/50000 (57%)]\tLoss: 0.324613, Accuracy: 89.84\n",
      "Train Epoch: 24 [26880/50000 (60%)]\tLoss: 0.269068, Accuracy: 91.41\n",
      "Train Epoch: 24 [28160/50000 (62%)]\tLoss: 0.242398, Accuracy: 92.19\n",
      "Train Epoch: 24 [29440/50000 (65%)]\tLoss: 0.289330, Accuracy: 90.23\n",
      "Train Epoch: 24 [30720/50000 (68%)]\tLoss: 0.246545, Accuracy: 90.62\n",
      "Train Epoch: 24 [32000/50000 (71%)]\tLoss: 0.218228, Accuracy: 92.97\n",
      "Train Epoch: 24 [33280/50000 (74%)]\tLoss: 0.224877, Accuracy: 92.97\n",
      "Train Epoch: 24 [34560/50000 (77%)]\tLoss: 0.251772, Accuracy: 90.62\n",
      "Train Epoch: 24 [35840/50000 (80%)]\tLoss: 0.273903, Accuracy: 90.62\n",
      "Train Epoch: 24 [37120/50000 (82%)]\tLoss: 0.223992, Accuracy: 90.62\n",
      "Train Epoch: 24 [38400/50000 (85%)]\tLoss: 0.246633, Accuracy: 89.84\n",
      "Train Epoch: 24 [39680/50000 (88%)]\tLoss: 0.212731, Accuracy: 92.58\n",
      "Train Epoch: 24 [40960/50000 (91%)]\tLoss: 0.271578, Accuracy: 89.45\n",
      "Train Epoch: 24 [42240/50000 (94%)]\tLoss: 0.249905, Accuracy: 91.02\n",
      "Train Epoch: 24 [43520/50000 (97%)]\tLoss: 0.227919, Accuracy: 91.02\n",
      "Train Epoch: 24 [35000/50000 (99%)]\tLoss: 0.199029, Accuracy: 94.50\n",
      "\n",
      "Validation set: Average loss: 0.3798, Accuracy: 4373/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.451006650924683 s]\n",
      "Train Epoch: 25 [0/50000 (0%)]\tLoss: 0.200754, Accuracy: 94.14\n",
      "Train Epoch: 25 [1280/50000 (3%)]\tLoss: 0.186951, Accuracy: 93.75\n",
      "Train Epoch: 25 [2560/50000 (6%)]\tLoss: 0.246766, Accuracy: 91.41\n",
      "Train Epoch: 25 [3840/50000 (9%)]\tLoss: 0.212698, Accuracy: 92.97\n",
      "Train Epoch: 25 [5120/50000 (11%)]\tLoss: 0.289333, Accuracy: 88.67\n",
      "Train Epoch: 25 [6400/50000 (14%)]\tLoss: 0.283390, Accuracy: 90.62\n",
      "Train Epoch: 25 [7680/50000 (17%)]\tLoss: 0.211411, Accuracy: 94.92\n",
      "Train Epoch: 25 [8960/50000 (20%)]\tLoss: 0.211376, Accuracy: 93.75\n",
      "Train Epoch: 25 [10240/50000 (23%)]\tLoss: 0.234247, Accuracy: 93.36\n",
      "Train Epoch: 25 [11520/50000 (26%)]\tLoss: 0.255153, Accuracy: 91.80\n",
      "Train Epoch: 25 [12800/50000 (28%)]\tLoss: 0.193812, Accuracy: 91.80\n",
      "Train Epoch: 25 [14080/50000 (31%)]\tLoss: 0.242637, Accuracy: 90.62\n",
      "Train Epoch: 25 [15360/50000 (34%)]\tLoss: 0.272102, Accuracy: 91.41\n",
      "Train Epoch: 25 [16640/50000 (37%)]\tLoss: 0.236995, Accuracy: 91.80\n",
      "Train Epoch: 25 [17920/50000 (40%)]\tLoss: 0.207463, Accuracy: 92.19\n",
      "Train Epoch: 25 [19200/50000 (43%)]\tLoss: 0.262861, Accuracy: 90.62\n",
      "Train Epoch: 25 [20480/50000 (45%)]\tLoss: 0.312696, Accuracy: 90.62\n",
      "Train Epoch: 25 [21760/50000 (48%)]\tLoss: 0.229171, Accuracy: 90.62\n",
      "Train Epoch: 25 [23040/50000 (51%)]\tLoss: 0.352135, Accuracy: 87.11\n",
      "Train Epoch: 25 [24320/50000 (54%)]\tLoss: 0.175333, Accuracy: 94.53\n",
      "Train Epoch: 25 [25600/50000 (57%)]\tLoss: 0.220289, Accuracy: 92.58\n",
      "Train Epoch: 25 [26880/50000 (60%)]\tLoss: 0.343843, Accuracy: 87.89\n",
      "Train Epoch: 25 [28160/50000 (62%)]\tLoss: 0.301403, Accuracy: 91.41\n",
      "Train Epoch: 25 [29440/50000 (65%)]\tLoss: 0.271020, Accuracy: 90.62\n",
      "Train Epoch: 25 [30720/50000 (68%)]\tLoss: 0.232181, Accuracy: 91.41\n",
      "Train Epoch: 25 [32000/50000 (71%)]\tLoss: 0.350255, Accuracy: 88.28\n",
      "Train Epoch: 25 [33280/50000 (74%)]\tLoss: 0.196483, Accuracy: 92.19\n",
      "Train Epoch: 25 [34560/50000 (77%)]\tLoss: 0.256356, Accuracy: 91.02\n",
      "Train Epoch: 25 [35840/50000 (80%)]\tLoss: 0.269686, Accuracy: 89.45\n",
      "Train Epoch: 25 [37120/50000 (82%)]\tLoss: 0.262280, Accuracy: 92.19\n",
      "Train Epoch: 25 [38400/50000 (85%)]\tLoss: 0.285518, Accuracy: 89.84\n",
      "Train Epoch: 25 [39680/50000 (88%)]\tLoss: 0.263735, Accuracy: 91.41\n",
      "Train Epoch: 25 [40960/50000 (91%)]\tLoss: 0.280510, Accuracy: 90.23\n",
      "Train Epoch: 25 [42240/50000 (94%)]\tLoss: 0.273674, Accuracy: 89.84\n",
      "Train Epoch: 25 [43520/50000 (97%)]\tLoss: 0.275659, Accuracy: 90.23\n",
      "Train Epoch: 25 [35000/50000 (99%)]\tLoss: 0.286252, Accuracy: 91.00\n",
      "\n",
      "Validation set: Average loss: 0.4624, Accuracy: 4283/5000 (85.00%)\n",
      "\n",
      "the time of this epoch:[21.478198766708374 s]\n",
      "Train Epoch: 26 [0/50000 (0%)]\tLoss: 0.147548, Accuracy: 96.09\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 26 [1280/50000 (3%)]\tLoss: 0.342268, Accuracy: 86.72\n",
      "Train Epoch: 26 [2560/50000 (6%)]\tLoss: 0.263716, Accuracy: 89.45\n",
      "Train Epoch: 26 [3840/50000 (9%)]\tLoss: 0.182385, Accuracy: 93.36\n",
      "Train Epoch: 26 [5120/50000 (11%)]\tLoss: 0.217192, Accuracy: 92.58\n",
      "Train Epoch: 26 [6400/50000 (14%)]\tLoss: 0.286073, Accuracy: 88.67\n",
      "Train Epoch: 26 [7680/50000 (17%)]\tLoss: 0.220696, Accuracy: 92.19\n",
      "Train Epoch: 26 [8960/50000 (20%)]\tLoss: 0.210260, Accuracy: 91.80\n",
      "Train Epoch: 26 [10240/50000 (23%)]\tLoss: 0.229457, Accuracy: 92.97\n",
      "Train Epoch: 26 [11520/50000 (26%)]\tLoss: 0.363508, Accuracy: 87.50\n",
      "Train Epoch: 26 [12800/50000 (28%)]\tLoss: 0.253410, Accuracy: 92.58\n",
      "Train Epoch: 26 [14080/50000 (31%)]\tLoss: 0.290617, Accuracy: 88.28\n",
      "Train Epoch: 26 [15360/50000 (34%)]\tLoss: 0.246841, Accuracy: 91.80\n",
      "Train Epoch: 26 [16640/50000 (37%)]\tLoss: 0.241133, Accuracy: 91.41\n",
      "Train Epoch: 26 [17920/50000 (40%)]\tLoss: 0.306086, Accuracy: 89.84\n",
      "Train Epoch: 26 [19200/50000 (43%)]\tLoss: 0.248210, Accuracy: 92.19\n",
      "Train Epoch: 26 [20480/50000 (45%)]\tLoss: 0.193454, Accuracy: 92.97\n",
      "Train Epoch: 26 [21760/50000 (48%)]\tLoss: 0.232766, Accuracy: 91.41\n",
      "Train Epoch: 26 [23040/50000 (51%)]\tLoss: 0.353769, Accuracy: 86.33\n",
      "Train Epoch: 26 [24320/50000 (54%)]\tLoss: 0.268964, Accuracy: 91.02\n",
      "Train Epoch: 26 [25600/50000 (57%)]\tLoss: 0.193880, Accuracy: 93.75\n",
      "Train Epoch: 26 [26880/50000 (60%)]\tLoss: 0.268088, Accuracy: 90.62\n",
      "Train Epoch: 26 [28160/50000 (62%)]\tLoss: 0.277527, Accuracy: 90.23\n",
      "Train Epoch: 26 [29440/50000 (65%)]\tLoss: 0.258355, Accuracy: 91.41\n",
      "Train Epoch: 26 [30720/50000 (68%)]\tLoss: 0.248887, Accuracy: 91.80\n",
      "Train Epoch: 26 [32000/50000 (71%)]\tLoss: 0.303720, Accuracy: 91.02\n",
      "Train Epoch: 26 [33280/50000 (74%)]\tLoss: 0.256993, Accuracy: 91.02\n",
      "Train Epoch: 26 [34560/50000 (77%)]\tLoss: 0.247613, Accuracy: 91.41\n",
      "Train Epoch: 26 [35840/50000 (80%)]\tLoss: 0.286074, Accuracy: 91.80\n",
      "Train Epoch: 26 [37120/50000 (82%)]\tLoss: 0.259795, Accuracy: 89.84\n",
      "Train Epoch: 26 [38400/50000 (85%)]\tLoss: 0.269473, Accuracy: 89.45\n",
      "Train Epoch: 26 [39680/50000 (88%)]\tLoss: 0.277565, Accuracy: 90.23\n",
      "Train Epoch: 26 [40960/50000 (91%)]\tLoss: 0.252074, Accuracy: 90.23\n",
      "Train Epoch: 26 [42240/50000 (94%)]\tLoss: 0.255129, Accuracy: 91.80\n",
      "Train Epoch: 26 [43520/50000 (97%)]\tLoss: 0.300416, Accuracy: 92.19\n",
      "Train Epoch: 26 [35000/50000 (99%)]\tLoss: 0.231485, Accuracy: 93.00\n",
      "\n",
      "Validation set: Average loss: 0.4142, Accuracy: 4351/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.475501775741577 s]\n",
      "Train Epoch: 27 [0/50000 (0%)]\tLoss: 0.249970, Accuracy: 91.80\n",
      "Train Epoch: 27 [1280/50000 (3%)]\tLoss: 0.190427, Accuracy: 93.75\n",
      "Train Epoch: 27 [2560/50000 (6%)]\tLoss: 0.258985, Accuracy: 92.19\n",
      "Train Epoch: 27 [3840/50000 (9%)]\tLoss: 0.205145, Accuracy: 92.19\n",
      "Train Epoch: 27 [5120/50000 (11%)]\tLoss: 0.297671, Accuracy: 91.02\n",
      "Train Epoch: 27 [6400/50000 (14%)]\tLoss: 0.266284, Accuracy: 89.06\n",
      "Train Epoch: 27 [7680/50000 (17%)]\tLoss: 0.222081, Accuracy: 90.62\n",
      "Train Epoch: 27 [8960/50000 (20%)]\tLoss: 0.213539, Accuracy: 92.97\n",
      "Train Epoch: 27 [10240/50000 (23%)]\tLoss: 0.177494, Accuracy: 93.75\n",
      "Train Epoch: 27 [11520/50000 (26%)]\tLoss: 0.196553, Accuracy: 94.14\n",
      "Train Epoch: 27 [12800/50000 (28%)]\tLoss: 0.262756, Accuracy: 90.62\n",
      "Train Epoch: 27 [14080/50000 (31%)]\tLoss: 0.264290, Accuracy: 90.62\n",
      "Train Epoch: 27 [15360/50000 (34%)]\tLoss: 0.204734, Accuracy: 93.75\n",
      "Train Epoch: 27 [16640/50000 (37%)]\tLoss: 0.152113, Accuracy: 94.53\n",
      "Train Epoch: 27 [17920/50000 (40%)]\tLoss: 0.205526, Accuracy: 92.97\n",
      "Train Epoch: 27 [19200/50000 (43%)]\tLoss: 0.318610, Accuracy: 89.06\n",
      "Train Epoch: 27 [20480/50000 (45%)]\tLoss: 0.267365, Accuracy: 90.62\n",
      "Train Epoch: 27 [21760/50000 (48%)]\tLoss: 0.213737, Accuracy: 93.36\n",
      "Train Epoch: 27 [23040/50000 (51%)]\tLoss: 0.246127, Accuracy: 91.41\n",
      "Train Epoch: 27 [24320/50000 (54%)]\tLoss: 0.324420, Accuracy: 87.50\n",
      "Train Epoch: 27 [25600/50000 (57%)]\tLoss: 0.252010, Accuracy: 92.19\n",
      "Train Epoch: 27 [26880/50000 (60%)]\tLoss: 0.288273, Accuracy: 91.02\n",
      "Train Epoch: 27 [28160/50000 (62%)]\tLoss: 0.240726, Accuracy: 88.28\n",
      "Train Epoch: 27 [29440/50000 (65%)]\tLoss: 0.184584, Accuracy: 93.75\n",
      "Train Epoch: 27 [30720/50000 (68%)]\tLoss: 0.203621, Accuracy: 92.19\n",
      "Train Epoch: 27 [32000/50000 (71%)]\tLoss: 0.241563, Accuracy: 91.02\n",
      "Train Epoch: 27 [33280/50000 (74%)]\tLoss: 0.209744, Accuracy: 94.14\n",
      "Train Epoch: 27 [34560/50000 (77%)]\tLoss: 0.354098, Accuracy: 90.23\n",
      "Train Epoch: 27 [35840/50000 (80%)]\tLoss: 0.256100, Accuracy: 91.80\n",
      "Train Epoch: 27 [37120/50000 (82%)]\tLoss: 0.303922, Accuracy: 87.50\n",
      "Train Epoch: 27 [38400/50000 (85%)]\tLoss: 0.206692, Accuracy: 92.58\n",
      "Train Epoch: 27 [39680/50000 (88%)]\tLoss: 0.188427, Accuracy: 91.02\n",
      "Train Epoch: 27 [40960/50000 (91%)]\tLoss: 0.224253, Accuracy: 92.97\n",
      "Train Epoch: 27 [42240/50000 (94%)]\tLoss: 0.214125, Accuracy: 92.19\n",
      "Train Epoch: 27 [43520/50000 (97%)]\tLoss: 0.260427, Accuracy: 91.80\n",
      "Train Epoch: 27 [35000/50000 (99%)]\tLoss: 0.292832, Accuracy: 89.00\n",
      "\n",
      "Validation set: Average loss: 0.4428, Accuracy: 4303/5000 (86.00%)\n",
      "\n",
      "the time of this epoch:[21.421133041381836 s]\n",
      "Train Epoch: 28 [0/50000 (0%)]\tLoss: 0.239706, Accuracy: 91.02\n",
      "Train Epoch: 28 [1280/50000 (3%)]\tLoss: 0.196978, Accuracy: 92.97\n",
      "Train Epoch: 28 [2560/50000 (6%)]\tLoss: 0.291859, Accuracy: 89.06\n",
      "Train Epoch: 28 [3840/50000 (9%)]\tLoss: 0.229728, Accuracy: 92.97\n",
      "Train Epoch: 28 [5120/50000 (11%)]\tLoss: 0.191837, Accuracy: 92.19\n",
      "Train Epoch: 28 [6400/50000 (14%)]\tLoss: 0.328245, Accuracy: 89.45\n",
      "Train Epoch: 28 [7680/50000 (17%)]\tLoss: 0.294489, Accuracy: 89.45\n",
      "Train Epoch: 28 [8960/50000 (20%)]\tLoss: 0.330778, Accuracy: 89.06\n",
      "Train Epoch: 28 [10240/50000 (23%)]\tLoss: 0.295892, Accuracy: 89.84\n",
      "Train Epoch: 28 [11520/50000 (26%)]\tLoss: 0.229310, Accuracy: 92.19\n",
      "Train Epoch: 28 [12800/50000 (28%)]\tLoss: 0.322331, Accuracy: 89.45\n",
      "Train Epoch: 28 [14080/50000 (31%)]\tLoss: 0.233903, Accuracy: 92.19\n",
      "Train Epoch: 28 [15360/50000 (34%)]\tLoss: 0.246803, Accuracy: 89.84\n",
      "Train Epoch: 28 [16640/50000 (37%)]\tLoss: 0.278120, Accuracy: 89.45\n",
      "Train Epoch: 28 [17920/50000 (40%)]\tLoss: 0.240199, Accuracy: 91.80\n",
      "Train Epoch: 28 [19200/50000 (43%)]\tLoss: 0.300720, Accuracy: 88.28\n",
      "Train Epoch: 28 [20480/50000 (45%)]\tLoss: 0.207697, Accuracy: 92.19\n",
      "Train Epoch: 28 [21760/50000 (48%)]\tLoss: 0.231161, Accuracy: 91.80\n",
      "Train Epoch: 28 [23040/50000 (51%)]\tLoss: 0.310202, Accuracy: 91.41\n",
      "Train Epoch: 28 [24320/50000 (54%)]\tLoss: 0.217281, Accuracy: 92.19\n",
      "Train Epoch: 28 [25600/50000 (57%)]\tLoss: 0.228916, Accuracy: 91.80\n",
      "Train Epoch: 28 [26880/50000 (60%)]\tLoss: 0.200682, Accuracy: 92.58\n",
      "Train Epoch: 28 [28160/50000 (62%)]\tLoss: 0.219926, Accuracy: 95.31\n",
      "Train Epoch: 28 [29440/50000 (65%)]\tLoss: 0.243642, Accuracy: 90.62\n",
      "Train Epoch: 28 [30720/50000 (68%)]\tLoss: 0.228211, Accuracy: 92.19\n",
      "Train Epoch: 28 [32000/50000 (71%)]\tLoss: 0.343055, Accuracy: 87.11\n",
      "Train Epoch: 28 [33280/50000 (74%)]\tLoss: 0.247325, Accuracy: 92.97\n",
      "Train Epoch: 28 [34560/50000 (77%)]\tLoss: 0.266899, Accuracy: 90.62\n",
      "Train Epoch: 28 [35840/50000 (80%)]\tLoss: 0.200232, Accuracy: 92.58\n",
      "Train Epoch: 28 [37120/50000 (82%)]\tLoss: 0.285283, Accuracy: 87.89\n",
      "Train Epoch: 28 [38400/50000 (85%)]\tLoss: 0.193009, Accuracy: 93.36\n",
      "Train Epoch: 28 [39680/50000 (88%)]\tLoss: 0.201420, Accuracy: 92.19\n",
      "Train Epoch: 28 [40960/50000 (91%)]\tLoss: 0.312542, Accuracy: 87.50\n",
      "Train Epoch: 28 [42240/50000 (94%)]\tLoss: 0.231360, Accuracy: 90.62\n",
      "Train Epoch: 28 [43520/50000 (97%)]\tLoss: 0.256324, Accuracy: 90.62\n",
      "Train Epoch: 28 [35000/50000 (99%)]\tLoss: 0.234649, Accuracy: 93.00\n",
      "\n",
      "Validation set: Average loss: 0.4064, Accuracy: 4353/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.38944411277771 s]\n",
      "Train Epoch: 29 [0/50000 (0%)]\tLoss: 0.245962, Accuracy: 89.84\n",
      "Train Epoch: 29 [1280/50000 (3%)]\tLoss: 0.226051, Accuracy: 91.80\n",
      "Train Epoch: 29 [2560/50000 (6%)]\tLoss: 0.239335, Accuracy: 90.62\n",
      "Train Epoch: 29 [3840/50000 (9%)]\tLoss: 0.159124, Accuracy: 94.92\n",
      "Train Epoch: 29 [5120/50000 (11%)]\tLoss: 0.282913, Accuracy: 90.62\n",
      "Train Epoch: 29 [6400/50000 (14%)]\tLoss: 0.208624, Accuracy: 92.58\n",
      "Train Epoch: 29 [7680/50000 (17%)]\tLoss: 0.244066, Accuracy: 90.23\n",
      "Train Epoch: 29 [8960/50000 (20%)]\tLoss: 0.312626, Accuracy: 92.19\n",
      "Train Epoch: 29 [10240/50000 (23%)]\tLoss: 0.217236, Accuracy: 91.41\n",
      "Train Epoch: 29 [11520/50000 (26%)]\tLoss: 0.215459, Accuracy: 91.80\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 29 [12800/50000 (28%)]\tLoss: 0.247632, Accuracy: 92.58\n",
      "Train Epoch: 29 [14080/50000 (31%)]\tLoss: 0.293280, Accuracy: 88.28\n",
      "Train Epoch: 29 [15360/50000 (34%)]\tLoss: 0.293673, Accuracy: 90.23\n",
      "Train Epoch: 29 [16640/50000 (37%)]\tLoss: 0.227685, Accuracy: 92.97\n",
      "Train Epoch: 29 [17920/50000 (40%)]\tLoss: 0.257773, Accuracy: 91.02\n",
      "Train Epoch: 29 [19200/50000 (43%)]\tLoss: 0.153936, Accuracy: 94.53\n",
      "Train Epoch: 29 [20480/50000 (45%)]\tLoss: 0.213975, Accuracy: 92.19\n",
      "Train Epoch: 29 [21760/50000 (48%)]\tLoss: 0.253461, Accuracy: 89.84\n",
      "Train Epoch: 29 [23040/50000 (51%)]\tLoss: 0.210595, Accuracy: 92.58\n",
      "Train Epoch: 29 [24320/50000 (54%)]\tLoss: 0.237949, Accuracy: 91.02\n",
      "Train Epoch: 29 [25600/50000 (57%)]\tLoss: 0.309837, Accuracy: 90.62\n",
      "Train Epoch: 29 [26880/50000 (60%)]\tLoss: 0.268749, Accuracy: 89.84\n",
      "Train Epoch: 29 [28160/50000 (62%)]\tLoss: 0.217280, Accuracy: 90.62\n",
      "Train Epoch: 29 [29440/50000 (65%)]\tLoss: 0.256739, Accuracy: 92.97\n",
      "Train Epoch: 29 [30720/50000 (68%)]\tLoss: 0.298796, Accuracy: 90.23\n",
      "Train Epoch: 29 [32000/50000 (71%)]\tLoss: 0.234304, Accuracy: 92.97\n",
      "Train Epoch: 29 [33280/50000 (74%)]\tLoss: 0.217541, Accuracy: 92.19\n",
      "Train Epoch: 29 [34560/50000 (77%)]\tLoss: 0.251723, Accuracy: 89.45\n",
      "Train Epoch: 29 [35840/50000 (80%)]\tLoss: 0.201366, Accuracy: 91.02\n",
      "Train Epoch: 29 [37120/50000 (82%)]\tLoss: 0.219381, Accuracy: 90.62\n",
      "Train Epoch: 29 [38400/50000 (85%)]\tLoss: 0.222643, Accuracy: 92.19\n",
      "Train Epoch: 29 [39680/50000 (88%)]\tLoss: 0.271135, Accuracy: 90.62\n",
      "Train Epoch: 29 [40960/50000 (91%)]\tLoss: 0.191434, Accuracy: 92.58\n",
      "Train Epoch: 29 [42240/50000 (94%)]\tLoss: 0.197386, Accuracy: 92.58\n",
      "Train Epoch: 29 [43520/50000 (97%)]\tLoss: 0.220495, Accuracy: 92.58\n",
      "Train Epoch: 29 [35000/50000 (99%)]\tLoss: 0.283859, Accuracy: 91.50\n",
      "\n",
      "Validation set: Average loss: 0.4178, Accuracy: 4335/5000 (86.00%)\n",
      "\n",
      "the time of this epoch:[21.40875816345215 s]\n",
      "Train Epoch: 30 [0/50000 (0%)]\tLoss: 0.305989, Accuracy: 91.02\n",
      "Train Epoch: 30 [1280/50000 (3%)]\tLoss: 0.255841, Accuracy: 90.62\n",
      "Train Epoch: 30 [2560/50000 (6%)]\tLoss: 0.194985, Accuracy: 92.97\n",
      "Train Epoch: 30 [3840/50000 (9%)]\tLoss: 0.212842, Accuracy: 94.14\n",
      "Train Epoch: 30 [5120/50000 (11%)]\tLoss: 0.253329, Accuracy: 90.62\n",
      "Train Epoch: 30 [6400/50000 (14%)]\tLoss: 0.177493, Accuracy: 93.75\n",
      "Train Epoch: 30 [7680/50000 (17%)]\tLoss: 0.208646, Accuracy: 93.75\n",
      "Train Epoch: 30 [8960/50000 (20%)]\tLoss: 0.182794, Accuracy: 94.53\n",
      "Train Epoch: 30 [10240/50000 (23%)]\tLoss: 0.233733, Accuracy: 92.19\n",
      "Train Epoch: 30 [11520/50000 (26%)]\tLoss: 0.229977, Accuracy: 91.80\n",
      "Train Epoch: 30 [12800/50000 (28%)]\tLoss: 0.211747, Accuracy: 91.80\n",
      "Train Epoch: 30 [14080/50000 (31%)]\tLoss: 0.264551, Accuracy: 89.06\n",
      "Train Epoch: 30 [15360/50000 (34%)]\tLoss: 0.194421, Accuracy: 92.58\n",
      "Train Epoch: 30 [16640/50000 (37%)]\tLoss: 0.211405, Accuracy: 93.75\n",
      "Train Epoch: 30 [17920/50000 (40%)]\tLoss: 0.338509, Accuracy: 86.33\n",
      "Train Epoch: 30 [19200/50000 (43%)]\tLoss: 0.234519, Accuracy: 92.97\n",
      "Train Epoch: 30 [20480/50000 (45%)]\tLoss: 0.197888, Accuracy: 94.14\n",
      "Train Epoch: 30 [21760/50000 (48%)]\tLoss: 0.241177, Accuracy: 92.19\n",
      "Train Epoch: 30 [23040/50000 (51%)]\tLoss: 0.181529, Accuracy: 95.31\n",
      "Train Epoch: 30 [24320/50000 (54%)]\tLoss: 0.214572, Accuracy: 92.58\n",
      "Train Epoch: 30 [25600/50000 (57%)]\tLoss: 0.368861, Accuracy: 88.28\n",
      "Train Epoch: 30 [26880/50000 (60%)]\tLoss: 0.225667, Accuracy: 91.02\n",
      "Train Epoch: 30 [28160/50000 (62%)]\tLoss: 0.307751, Accuracy: 89.84\n",
      "Train Epoch: 30 [29440/50000 (65%)]\tLoss: 0.274790, Accuracy: 90.62\n",
      "Train Epoch: 30 [30720/50000 (68%)]\tLoss: 0.228196, Accuracy: 91.80\n",
      "Train Epoch: 30 [32000/50000 (71%)]\tLoss: 0.248420, Accuracy: 90.23\n",
      "Train Epoch: 30 [33280/50000 (74%)]\tLoss: 0.304561, Accuracy: 89.06\n",
      "Train Epoch: 30 [34560/50000 (77%)]\tLoss: 0.208049, Accuracy: 91.80\n",
      "Train Epoch: 30 [35840/50000 (80%)]\tLoss: 0.176996, Accuracy: 94.14\n",
      "Train Epoch: 30 [37120/50000 (82%)]\tLoss: 0.261089, Accuracy: 92.58\n",
      "Train Epoch: 30 [38400/50000 (85%)]\tLoss: 0.272030, Accuracy: 91.80\n",
      "Train Epoch: 30 [39680/50000 (88%)]\tLoss: 0.215021, Accuracy: 93.36\n",
      "Train Epoch: 30 [40960/50000 (91%)]\tLoss: 0.257192, Accuracy: 88.67\n",
      "Train Epoch: 30 [42240/50000 (94%)]\tLoss: 0.181781, Accuracy: 92.97\n",
      "Train Epoch: 30 [43520/50000 (97%)]\tLoss: 0.205318, Accuracy: 93.75\n",
      "Train Epoch: 30 [35000/50000 (99%)]\tLoss: 0.218415, Accuracy: 91.00\n",
      "\n",
      "Validation set: Average loss: 0.3902, Accuracy: 4381/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.394972324371338 s]\n",
      "Train Epoch: 31 [0/50000 (0%)]\tLoss: 0.265061, Accuracy: 91.02\n",
      "Train Epoch: 31 [1280/50000 (3%)]\tLoss: 0.241685, Accuracy: 92.19\n",
      "Train Epoch: 31 [2560/50000 (6%)]\tLoss: 0.269748, Accuracy: 89.84\n",
      "Train Epoch: 31 [3840/50000 (9%)]\tLoss: 0.151323, Accuracy: 94.14\n",
      "Train Epoch: 31 [5120/50000 (11%)]\tLoss: 0.217357, Accuracy: 91.02\n",
      "Train Epoch: 31 [6400/50000 (14%)]\tLoss: 0.206817, Accuracy: 92.58\n",
      "Train Epoch: 31 [7680/50000 (17%)]\tLoss: 0.273881, Accuracy: 89.84\n",
      "Train Epoch: 31 [8960/50000 (20%)]\tLoss: 0.280135, Accuracy: 88.28\n",
      "Train Epoch: 31 [10240/50000 (23%)]\tLoss: 0.230267, Accuracy: 91.02\n",
      "Train Epoch: 31 [11520/50000 (26%)]\tLoss: 0.267566, Accuracy: 90.23\n",
      "Train Epoch: 31 [12800/50000 (28%)]\tLoss: 0.203611, Accuracy: 92.97\n",
      "Train Epoch: 31 [14080/50000 (31%)]\tLoss: 0.182261, Accuracy: 94.53\n",
      "Train Epoch: 31 [15360/50000 (34%)]\tLoss: 0.176232, Accuracy: 94.53\n",
      "Train Epoch: 31 [16640/50000 (37%)]\tLoss: 0.273063, Accuracy: 91.02\n",
      "Train Epoch: 31 [17920/50000 (40%)]\tLoss: 0.206769, Accuracy: 90.62\n",
      "Train Epoch: 31 [19200/50000 (43%)]\tLoss: 0.219395, Accuracy: 92.19\n",
      "Train Epoch: 31 [20480/50000 (45%)]\tLoss: 0.236786, Accuracy: 92.58\n",
      "Train Epoch: 31 [21760/50000 (48%)]\tLoss: 0.233218, Accuracy: 91.80\n",
      "Train Epoch: 31 [23040/50000 (51%)]\tLoss: 0.262288, Accuracy: 91.02\n",
      "Train Epoch: 31 [24320/50000 (54%)]\tLoss: 0.260037, Accuracy: 93.36\n",
      "Train Epoch: 31 [25600/50000 (57%)]\tLoss: 0.231091, Accuracy: 91.41\n",
      "Train Epoch: 31 [26880/50000 (60%)]\tLoss: 0.218312, Accuracy: 91.41\n",
      "Train Epoch: 31 [28160/50000 (62%)]\tLoss: 0.209095, Accuracy: 92.97\n",
      "Train Epoch: 31 [29440/50000 (65%)]\tLoss: 0.206214, Accuracy: 91.80\n",
      "Train Epoch: 31 [30720/50000 (68%)]\tLoss: 0.258639, Accuracy: 91.02\n",
      "Train Epoch: 31 [32000/50000 (71%)]\tLoss: 0.284128, Accuracy: 92.58\n",
      "Train Epoch: 31 [33280/50000 (74%)]\tLoss: 0.226300, Accuracy: 91.02\n",
      "Train Epoch: 31 [34560/50000 (77%)]\tLoss: 0.216247, Accuracy: 94.14\n",
      "Train Epoch: 31 [35840/50000 (80%)]\tLoss: 0.266428, Accuracy: 88.67\n",
      "Train Epoch: 31 [37120/50000 (82%)]\tLoss: 0.191822, Accuracy: 94.92\n",
      "Train Epoch: 31 [38400/50000 (85%)]\tLoss: 0.207224, Accuracy: 92.58\n",
      "Train Epoch: 31 [39680/50000 (88%)]\tLoss: 0.311615, Accuracy: 91.41\n",
      "Train Epoch: 31 [40960/50000 (91%)]\tLoss: 0.242739, Accuracy: 91.02\n",
      "Train Epoch: 31 [42240/50000 (94%)]\tLoss: 0.269800, Accuracy: 89.06\n",
      "Train Epoch: 31 [43520/50000 (97%)]\tLoss: 0.220799, Accuracy: 93.36\n",
      "Train Epoch: 31 [35000/50000 (99%)]\tLoss: 0.292479, Accuracy: 91.00\n",
      "\n",
      "Validation set: Average loss: 0.3716, Accuracy: 4403/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.391059637069702 s]\n",
      "Train Epoch: 32 [0/50000 (0%)]\tLoss: 0.174602, Accuracy: 94.92\n",
      "Train Epoch: 32 [1280/50000 (3%)]\tLoss: 0.229895, Accuracy: 91.41\n",
      "Train Epoch: 32 [2560/50000 (6%)]\tLoss: 0.194071, Accuracy: 92.58\n",
      "Train Epoch: 32 [3840/50000 (9%)]\tLoss: 0.257893, Accuracy: 91.02\n",
      "Train Epoch: 32 [5120/50000 (11%)]\tLoss: 0.258311, Accuracy: 91.02\n",
      "Train Epoch: 32 [6400/50000 (14%)]\tLoss: 0.164116, Accuracy: 94.53\n",
      "Train Epoch: 32 [7680/50000 (17%)]\tLoss: 0.230639, Accuracy: 91.80\n",
      "Train Epoch: 32 [8960/50000 (20%)]\tLoss: 0.219949, Accuracy: 92.19\n",
      "Train Epoch: 32 [10240/50000 (23%)]\tLoss: 0.223167, Accuracy: 91.80\n",
      "Train Epoch: 32 [11520/50000 (26%)]\tLoss: 0.333204, Accuracy: 89.84\n",
      "Train Epoch: 32 [12800/50000 (28%)]\tLoss: 0.167628, Accuracy: 95.31\n",
      "Train Epoch: 32 [14080/50000 (31%)]\tLoss: 0.312490, Accuracy: 88.67\n",
      "Train Epoch: 32 [15360/50000 (34%)]\tLoss: 0.164126, Accuracy: 94.92\n",
      "Train Epoch: 32 [16640/50000 (37%)]\tLoss: 0.194898, Accuracy: 93.36\n",
      "Train Epoch: 32 [17920/50000 (40%)]\tLoss: 0.211067, Accuracy: 92.19\n",
      "Train Epoch: 32 [19200/50000 (43%)]\tLoss: 0.234289, Accuracy: 90.62\n",
      "Train Epoch: 32 [20480/50000 (45%)]\tLoss: 0.213751, Accuracy: 93.36\n",
      "Train Epoch: 32 [21760/50000 (48%)]\tLoss: 0.193636, Accuracy: 94.53\n",
      "Train Epoch: 32 [23040/50000 (51%)]\tLoss: 0.255769, Accuracy: 91.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 32 [24320/50000 (54%)]\tLoss: 0.194132, Accuracy: 92.97\n",
      "Train Epoch: 32 [25600/50000 (57%)]\tLoss: 0.263106, Accuracy: 91.41\n",
      "Train Epoch: 32 [26880/50000 (60%)]\tLoss: 0.300133, Accuracy: 89.84\n",
      "Train Epoch: 32 [28160/50000 (62%)]\tLoss: 0.214539, Accuracy: 93.75\n",
      "Train Epoch: 32 [29440/50000 (65%)]\tLoss: 0.202845, Accuracy: 93.36\n",
      "Train Epoch: 32 [30720/50000 (68%)]\tLoss: 0.208586, Accuracy: 91.41\n",
      "Train Epoch: 32 [32000/50000 (71%)]\tLoss: 0.201535, Accuracy: 92.19\n",
      "Train Epoch: 32 [33280/50000 (74%)]\tLoss: 0.197197, Accuracy: 90.23\n",
      "Train Epoch: 32 [34560/50000 (77%)]\tLoss: 0.244330, Accuracy: 91.41\n",
      "Train Epoch: 32 [35840/50000 (80%)]\tLoss: 0.253096, Accuracy: 89.84\n",
      "Train Epoch: 32 [37120/50000 (82%)]\tLoss: 0.210273, Accuracy: 94.53\n",
      "Train Epoch: 32 [38400/50000 (85%)]\tLoss: 0.232215, Accuracy: 91.41\n",
      "Train Epoch: 32 [39680/50000 (88%)]\tLoss: 0.314824, Accuracy: 91.02\n",
      "Train Epoch: 32 [40960/50000 (91%)]\tLoss: 0.229243, Accuracy: 91.02\n",
      "Train Epoch: 32 [42240/50000 (94%)]\tLoss: 0.244197, Accuracy: 92.58\n",
      "Train Epoch: 32 [43520/50000 (97%)]\tLoss: 0.241665, Accuracy: 91.80\n",
      "Train Epoch: 32 [35000/50000 (99%)]\tLoss: 0.257084, Accuracy: 89.50\n",
      "\n",
      "Validation set: Average loss: 0.4167, Accuracy: 4351/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.41021180152893 s]\n",
      "Train Epoch: 33 [0/50000 (0%)]\tLoss: 0.183826, Accuracy: 94.92\n",
      "Train Epoch: 33 [1280/50000 (3%)]\tLoss: 0.196548, Accuracy: 92.97\n",
      "Train Epoch: 33 [2560/50000 (6%)]\tLoss: 0.186477, Accuracy: 93.75\n",
      "Train Epoch: 33 [3840/50000 (9%)]\tLoss: 0.187832, Accuracy: 91.80\n",
      "Train Epoch: 33 [5120/50000 (11%)]\tLoss: 0.228936, Accuracy: 91.41\n",
      "Train Epoch: 33 [6400/50000 (14%)]\tLoss: 0.255283, Accuracy: 91.80\n",
      "Train Epoch: 33 [7680/50000 (17%)]\tLoss: 0.215575, Accuracy: 94.53\n",
      "Train Epoch: 33 [8960/50000 (20%)]\tLoss: 0.135622, Accuracy: 96.09\n",
      "Train Epoch: 33 [10240/50000 (23%)]\tLoss: 0.194260, Accuracy: 93.75\n",
      "Train Epoch: 33 [11520/50000 (26%)]\tLoss: 0.227432, Accuracy: 91.41\n",
      "Train Epoch: 33 [12800/50000 (28%)]\tLoss: 0.210839, Accuracy: 94.14\n",
      "Train Epoch: 33 [14080/50000 (31%)]\tLoss: 0.210664, Accuracy: 94.14\n",
      "Train Epoch: 33 [15360/50000 (34%)]\tLoss: 0.225527, Accuracy: 91.02\n",
      "Train Epoch: 33 [16640/50000 (37%)]\tLoss: 0.191335, Accuracy: 93.75\n",
      "Train Epoch: 33 [17920/50000 (40%)]\tLoss: 0.152239, Accuracy: 94.53\n",
      "Train Epoch: 33 [19200/50000 (43%)]\tLoss: 0.224851, Accuracy: 92.58\n",
      "Train Epoch: 33 [20480/50000 (45%)]\tLoss: 0.246040, Accuracy: 91.41\n",
      "Train Epoch: 33 [21760/50000 (48%)]\tLoss: 0.194502, Accuracy: 91.41\n",
      "Train Epoch: 33 [23040/50000 (51%)]\tLoss: 0.169623, Accuracy: 93.75\n",
      "Train Epoch: 33 [24320/50000 (54%)]\tLoss: 0.224875, Accuracy: 91.80\n",
      "Train Epoch: 33 [25600/50000 (57%)]\tLoss: 0.200045, Accuracy: 93.36\n",
      "Train Epoch: 33 [26880/50000 (60%)]\tLoss: 0.293873, Accuracy: 89.06\n",
      "Train Epoch: 33 [28160/50000 (62%)]\tLoss: 0.281246, Accuracy: 92.19\n",
      "Train Epoch: 33 [29440/50000 (65%)]\tLoss: 0.214038, Accuracy: 91.02\n",
      "Train Epoch: 33 [30720/50000 (68%)]\tLoss: 0.187352, Accuracy: 92.19\n",
      "Train Epoch: 33 [32000/50000 (71%)]\tLoss: 0.107565, Accuracy: 98.83\n",
      "Train Epoch: 33 [33280/50000 (74%)]\tLoss: 0.174077, Accuracy: 93.75\n",
      "Train Epoch: 33 [34560/50000 (77%)]\tLoss: 0.252885, Accuracy: 92.97\n",
      "Train Epoch: 33 [35840/50000 (80%)]\tLoss: 0.287143, Accuracy: 91.80\n",
      "Train Epoch: 33 [37120/50000 (82%)]\tLoss: 0.237337, Accuracy: 92.19\n",
      "Train Epoch: 33 [38400/50000 (85%)]\tLoss: 0.259131, Accuracy: 89.84\n",
      "Train Epoch: 33 [39680/50000 (88%)]\tLoss: 0.258598, Accuracy: 90.62\n",
      "Train Epoch: 33 [40960/50000 (91%)]\tLoss: 0.303387, Accuracy: 90.23\n",
      "Train Epoch: 33 [42240/50000 (94%)]\tLoss: 0.269490, Accuracy: 90.23\n",
      "Train Epoch: 33 [43520/50000 (97%)]\tLoss: 0.252953, Accuracy: 92.58\n",
      "Train Epoch: 33 [35000/50000 (99%)]\tLoss: 0.314521, Accuracy: 87.00\n",
      "\n",
      "Validation set: Average loss: 0.4116, Accuracy: 4355/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.386770248413086 s]\n",
      "Train Epoch: 34 [0/50000 (0%)]\tLoss: 0.150580, Accuracy: 95.31\n",
      "Train Epoch: 34 [1280/50000 (3%)]\tLoss: 0.219939, Accuracy: 91.41\n",
      "Train Epoch: 34 [2560/50000 (6%)]\tLoss: 0.193599, Accuracy: 93.75\n",
      "Train Epoch: 34 [3840/50000 (9%)]\tLoss: 0.191988, Accuracy: 92.19\n",
      "Train Epoch: 34 [5120/50000 (11%)]\tLoss: 0.178573, Accuracy: 93.75\n",
      "Train Epoch: 34 [6400/50000 (14%)]\tLoss: 0.242270, Accuracy: 92.19\n",
      "Train Epoch: 34 [7680/50000 (17%)]\tLoss: 0.233737, Accuracy: 92.19\n",
      "Train Epoch: 34 [8960/50000 (20%)]\tLoss: 0.162136, Accuracy: 94.14\n",
      "Train Epoch: 34 [10240/50000 (23%)]\tLoss: 0.218433, Accuracy: 94.14\n",
      "Train Epoch: 34 [11520/50000 (26%)]\tLoss: 0.219249, Accuracy: 92.58\n",
      "Train Epoch: 34 [12800/50000 (28%)]\tLoss: 0.164581, Accuracy: 92.58\n",
      "Train Epoch: 34 [14080/50000 (31%)]\tLoss: 0.148997, Accuracy: 92.97\n",
      "Train Epoch: 34 [15360/50000 (34%)]\tLoss: 0.216194, Accuracy: 92.19\n",
      "Train Epoch: 34 [16640/50000 (37%)]\tLoss: 0.271210, Accuracy: 91.02\n",
      "Train Epoch: 34 [17920/50000 (40%)]\tLoss: 0.171858, Accuracy: 94.53\n",
      "Train Epoch: 34 [19200/50000 (43%)]\tLoss: 0.229965, Accuracy: 91.41\n",
      "Train Epoch: 34 [20480/50000 (45%)]\tLoss: 0.207752, Accuracy: 91.41\n",
      "Train Epoch: 34 [21760/50000 (48%)]\tLoss: 0.252263, Accuracy: 92.58\n",
      "Train Epoch: 34 [23040/50000 (51%)]\tLoss: 0.264942, Accuracy: 92.19\n",
      "Train Epoch: 34 [24320/50000 (54%)]\tLoss: 0.157385, Accuracy: 94.14\n",
      "Train Epoch: 34 [25600/50000 (57%)]\tLoss: 0.233871, Accuracy: 89.06\n",
      "Train Epoch: 34 [26880/50000 (60%)]\tLoss: 0.245207, Accuracy: 91.80\n",
      "Train Epoch: 34 [28160/50000 (62%)]\tLoss: 0.204793, Accuracy: 91.80\n",
      "Train Epoch: 34 [29440/50000 (65%)]\tLoss: 0.280688, Accuracy: 88.67\n",
      "Train Epoch: 34 [30720/50000 (68%)]\tLoss: 0.218562, Accuracy: 92.19\n",
      "Train Epoch: 34 [32000/50000 (71%)]\tLoss: 0.179222, Accuracy: 91.80\n",
      "Train Epoch: 34 [33280/50000 (74%)]\tLoss: 0.275787, Accuracy: 91.02\n",
      "Train Epoch: 34 [34560/50000 (77%)]\tLoss: 0.228654, Accuracy: 92.58\n",
      "Train Epoch: 34 [35840/50000 (80%)]\tLoss: 0.241747, Accuracy: 90.62\n",
      "Train Epoch: 34 [37120/50000 (82%)]\tLoss: 0.254866, Accuracy: 90.62\n",
      "Train Epoch: 34 [38400/50000 (85%)]\tLoss: 0.229165, Accuracy: 94.14\n",
      "Train Epoch: 34 [39680/50000 (88%)]\tLoss: 0.190677, Accuracy: 93.75\n",
      "Train Epoch: 34 [40960/50000 (91%)]\tLoss: 0.175023, Accuracy: 92.97\n",
      "Train Epoch: 34 [42240/50000 (94%)]\tLoss: 0.225476, Accuracy: 92.58\n",
      "Train Epoch: 34 [43520/50000 (97%)]\tLoss: 0.179013, Accuracy: 92.97\n",
      "Train Epoch: 34 [35000/50000 (99%)]\tLoss: 0.243872, Accuracy: 93.00\n",
      "\n",
      "Validation set: Average loss: 0.4218, Accuracy: 4317/5000 (86.00%)\n",
      "\n",
      "the time of this epoch:[21.36181879043579 s]\n",
      "Train Epoch: 35 [0/50000 (0%)]\tLoss: 0.219404, Accuracy: 91.80\n",
      "Train Epoch: 35 [1280/50000 (3%)]\tLoss: 0.147250, Accuracy: 94.92\n",
      "Train Epoch: 35 [2560/50000 (6%)]\tLoss: 0.238869, Accuracy: 91.02\n",
      "Train Epoch: 35 [3840/50000 (9%)]\tLoss: 0.252242, Accuracy: 89.45\n",
      "Train Epoch: 35 [5120/50000 (11%)]\tLoss: 0.178876, Accuracy: 94.53\n",
      "Train Epoch: 35 [6400/50000 (14%)]\tLoss: 0.234600, Accuracy: 91.41\n",
      "Train Epoch: 35 [7680/50000 (17%)]\tLoss: 0.161188, Accuracy: 93.75\n",
      "Train Epoch: 35 [8960/50000 (20%)]\tLoss: 0.198304, Accuracy: 92.97\n",
      "Train Epoch: 35 [10240/50000 (23%)]\tLoss: 0.162071, Accuracy: 94.92\n",
      "Train Epoch: 35 [11520/50000 (26%)]\tLoss: 0.177148, Accuracy: 95.31\n",
      "Train Epoch: 35 [12800/50000 (28%)]\tLoss: 0.270284, Accuracy: 90.62\n",
      "Train Epoch: 35 [14080/50000 (31%)]\tLoss: 0.227000, Accuracy: 91.41\n",
      "Train Epoch: 35 [15360/50000 (34%)]\tLoss: 0.258748, Accuracy: 91.80\n",
      "Train Epoch: 35 [16640/50000 (37%)]\tLoss: 0.198960, Accuracy: 92.97\n",
      "Train Epoch: 35 [17920/50000 (40%)]\tLoss: 0.206223, Accuracy: 92.97\n",
      "Train Epoch: 35 [19200/50000 (43%)]\tLoss: 0.198736, Accuracy: 92.58\n",
      "Train Epoch: 35 [20480/50000 (45%)]\tLoss: 0.155902, Accuracy: 94.14\n",
      "Train Epoch: 35 [21760/50000 (48%)]\tLoss: 0.160082, Accuracy: 92.97\n",
      "Train Epoch: 35 [23040/50000 (51%)]\tLoss: 0.250729, Accuracy: 91.02\n",
      "Train Epoch: 35 [24320/50000 (54%)]\tLoss: 0.145476, Accuracy: 94.92\n",
      "Train Epoch: 35 [25600/50000 (57%)]\tLoss: 0.163269, Accuracy: 94.14\n",
      "Train Epoch: 35 [26880/50000 (60%)]\tLoss: 0.265167, Accuracy: 91.02\n",
      "Train Epoch: 35 [28160/50000 (62%)]\tLoss: 0.251431, Accuracy: 91.80\n",
      "Train Epoch: 35 [29440/50000 (65%)]\tLoss: 0.206659, Accuracy: 90.62\n",
      "Train Epoch: 35 [30720/50000 (68%)]\tLoss: 0.222103, Accuracy: 90.23\n",
      "Train Epoch: 35 [32000/50000 (71%)]\tLoss: 0.218456, Accuracy: 91.02\n",
      "Train Epoch: 35 [33280/50000 (74%)]\tLoss: 0.180617, Accuracy: 92.58\n",
      "Train Epoch: 35 [34560/50000 (77%)]\tLoss: 0.210239, Accuracy: 92.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 35 [35840/50000 (80%)]\tLoss: 0.190513, Accuracy: 92.97\n",
      "Train Epoch: 35 [37120/50000 (82%)]\tLoss: 0.159127, Accuracy: 93.75\n",
      "Train Epoch: 35 [38400/50000 (85%)]\tLoss: 0.251494, Accuracy: 91.80\n",
      "Train Epoch: 35 [39680/50000 (88%)]\tLoss: 0.181698, Accuracy: 92.58\n",
      "Train Epoch: 35 [40960/50000 (91%)]\tLoss: 0.174544, Accuracy: 94.53\n",
      "Train Epoch: 35 [42240/50000 (94%)]\tLoss: 0.195041, Accuracy: 93.75\n",
      "Train Epoch: 35 [43520/50000 (97%)]\tLoss: 0.242345, Accuracy: 90.62\n",
      "Train Epoch: 35 [35000/50000 (99%)]\tLoss: 0.196269, Accuracy: 91.50\n",
      "\n",
      "Validation set: Average loss: 0.3879, Accuracy: 4372/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.399486780166626 s]\n",
      "Train Epoch: 36 [0/50000 (0%)]\tLoss: 0.149582, Accuracy: 94.53\n",
      "Train Epoch: 36 [1280/50000 (3%)]\tLoss: 0.222138, Accuracy: 91.41\n",
      "Train Epoch: 36 [2560/50000 (6%)]\tLoss: 0.209770, Accuracy: 94.14\n",
      "Train Epoch: 36 [3840/50000 (9%)]\tLoss: 0.188243, Accuracy: 93.75\n",
      "Train Epoch: 36 [5120/50000 (11%)]\tLoss: 0.164061, Accuracy: 93.75\n",
      "Train Epoch: 36 [6400/50000 (14%)]\tLoss: 0.269958, Accuracy: 89.84\n",
      "Train Epoch: 36 [7680/50000 (17%)]\tLoss: 0.171145, Accuracy: 94.92\n",
      "Train Epoch: 36 [8960/50000 (20%)]\tLoss: 0.145443, Accuracy: 94.14\n",
      "Train Epoch: 36 [10240/50000 (23%)]\tLoss: 0.182079, Accuracy: 93.75\n",
      "Train Epoch: 36 [11520/50000 (26%)]\tLoss: 0.179189, Accuracy: 93.36\n",
      "Train Epoch: 36 [12800/50000 (28%)]\tLoss: 0.226979, Accuracy: 91.41\n",
      "Train Epoch: 36 [14080/50000 (31%)]\tLoss: 0.171177, Accuracy: 94.92\n",
      "Train Epoch: 36 [15360/50000 (34%)]\tLoss: 0.298173, Accuracy: 89.45\n",
      "Train Epoch: 36 [16640/50000 (37%)]\tLoss: 0.219389, Accuracy: 94.14\n",
      "Train Epoch: 36 [17920/50000 (40%)]\tLoss: 0.175804, Accuracy: 93.36\n",
      "Train Epoch: 36 [19200/50000 (43%)]\tLoss: 0.190052, Accuracy: 92.97\n",
      "Train Epoch: 36 [20480/50000 (45%)]\tLoss: 0.229043, Accuracy: 91.80\n",
      "Train Epoch: 36 [21760/50000 (48%)]\tLoss: 0.153134, Accuracy: 96.09\n",
      "Train Epoch: 36 [23040/50000 (51%)]\tLoss: 0.303003, Accuracy: 89.06\n",
      "Train Epoch: 36 [24320/50000 (54%)]\tLoss: 0.236597, Accuracy: 92.58\n",
      "Train Epoch: 36 [25600/50000 (57%)]\tLoss: 0.248653, Accuracy: 91.02\n",
      "Train Epoch: 36 [26880/50000 (60%)]\tLoss: 0.129824, Accuracy: 95.31\n",
      "Train Epoch: 36 [28160/50000 (62%)]\tLoss: 0.243777, Accuracy: 92.58\n",
      "Train Epoch: 36 [29440/50000 (65%)]\tLoss: 0.205090, Accuracy: 93.36\n",
      "Train Epoch: 36 [30720/50000 (68%)]\tLoss: 0.302484, Accuracy: 87.11\n",
      "Train Epoch: 36 [32000/50000 (71%)]\tLoss: 0.205532, Accuracy: 92.19\n",
      "Train Epoch: 36 [33280/50000 (74%)]\tLoss: 0.206916, Accuracy: 92.58\n",
      "Train Epoch: 36 [34560/50000 (77%)]\tLoss: 0.202296, Accuracy: 93.75\n",
      "Train Epoch: 36 [35840/50000 (80%)]\tLoss: 0.255302, Accuracy: 90.62\n",
      "Train Epoch: 36 [37120/50000 (82%)]\tLoss: 0.172779, Accuracy: 93.36\n",
      "Train Epoch: 36 [38400/50000 (85%)]\tLoss: 0.184042, Accuracy: 93.75\n",
      "Train Epoch: 36 [39680/50000 (88%)]\tLoss: 0.277487, Accuracy: 91.80\n",
      "Train Epoch: 36 [40960/50000 (91%)]\tLoss: 0.154620, Accuracy: 94.53\n",
      "Train Epoch: 36 [42240/50000 (94%)]\tLoss: 0.170921, Accuracy: 93.36\n",
      "Train Epoch: 36 [43520/50000 (97%)]\tLoss: 0.320774, Accuracy: 89.84\n",
      "Train Epoch: 36 [35000/50000 (99%)]\tLoss: 0.269541, Accuracy: 90.00\n",
      "\n",
      "Validation set: Average loss: 0.3868, Accuracy: 4392/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.415705919265747 s]\n",
      "Train Epoch: 37 [0/50000 (0%)]\tLoss: 0.190351, Accuracy: 93.75\n",
      "Train Epoch: 37 [1280/50000 (3%)]\tLoss: 0.254701, Accuracy: 92.19\n",
      "Train Epoch: 37 [2560/50000 (6%)]\tLoss: 0.223359, Accuracy: 92.58\n",
      "Train Epoch: 37 [3840/50000 (9%)]\tLoss: 0.239432, Accuracy: 93.36\n",
      "Train Epoch: 37 [5120/50000 (11%)]\tLoss: 0.193333, Accuracy: 91.41\n",
      "Train Epoch: 37 [6400/50000 (14%)]\tLoss: 0.225747, Accuracy: 92.58\n",
      "Train Epoch: 37 [7680/50000 (17%)]\tLoss: 0.208836, Accuracy: 92.58\n",
      "Train Epoch: 37 [8960/50000 (20%)]\tLoss: 0.175413, Accuracy: 94.14\n",
      "Train Epoch: 37 [10240/50000 (23%)]\tLoss: 0.192185, Accuracy: 93.36\n",
      "Train Epoch: 37 [11520/50000 (26%)]\tLoss: 0.225234, Accuracy: 92.58\n",
      "Train Epoch: 37 [12800/50000 (28%)]\tLoss: 0.190812, Accuracy: 95.70\n",
      "Train Epoch: 37 [14080/50000 (31%)]\tLoss: 0.199344, Accuracy: 92.19\n",
      "Train Epoch: 37 [15360/50000 (34%)]\tLoss: 0.196542, Accuracy: 92.58\n",
      "Train Epoch: 37 [16640/50000 (37%)]\tLoss: 0.187600, Accuracy: 93.75\n",
      "Train Epoch: 37 [17920/50000 (40%)]\tLoss: 0.190811, Accuracy: 94.14\n",
      "Train Epoch: 37 [19200/50000 (43%)]\tLoss: 0.227731, Accuracy: 91.41\n",
      "Train Epoch: 37 [20480/50000 (45%)]\tLoss: 0.176273, Accuracy: 93.75\n",
      "Train Epoch: 37 [21760/50000 (48%)]\tLoss: 0.244849, Accuracy: 91.41\n",
      "Train Epoch: 37 [23040/50000 (51%)]\tLoss: 0.154888, Accuracy: 95.70\n",
      "Train Epoch: 37 [24320/50000 (54%)]\tLoss: 0.273955, Accuracy: 91.02\n",
      "Train Epoch: 37 [25600/50000 (57%)]\tLoss: 0.171620, Accuracy: 92.97\n",
      "Train Epoch: 37 [26880/50000 (60%)]\tLoss: 0.163224, Accuracy: 94.14\n",
      "Train Epoch: 37 [28160/50000 (62%)]\tLoss: 0.223597, Accuracy: 91.80\n",
      "Train Epoch: 37 [29440/50000 (65%)]\tLoss: 0.161083, Accuracy: 95.31\n",
      "Train Epoch: 37 [30720/50000 (68%)]\tLoss: 0.204459, Accuracy: 93.36\n",
      "Train Epoch: 37 [32000/50000 (71%)]\tLoss: 0.175924, Accuracy: 93.36\n",
      "Train Epoch: 37 [33280/50000 (74%)]\tLoss: 0.217391, Accuracy: 93.36\n",
      "Train Epoch: 37 [34560/50000 (77%)]\tLoss: 0.285936, Accuracy: 89.06\n",
      "Train Epoch: 37 [35840/50000 (80%)]\tLoss: 0.204380, Accuracy: 92.19\n",
      "Train Epoch: 37 [37120/50000 (82%)]\tLoss: 0.194123, Accuracy: 92.58\n",
      "Train Epoch: 37 [38400/50000 (85%)]\tLoss: 0.181268, Accuracy: 92.97\n",
      "Train Epoch: 37 [39680/50000 (88%)]\tLoss: 0.195434, Accuracy: 90.23\n",
      "Train Epoch: 37 [40960/50000 (91%)]\tLoss: 0.212808, Accuracy: 92.19\n",
      "Train Epoch: 37 [42240/50000 (94%)]\tLoss: 0.146592, Accuracy: 95.70\n",
      "Train Epoch: 37 [43520/50000 (97%)]\tLoss: 0.200943, Accuracy: 92.19\n",
      "Train Epoch: 37 [35000/50000 (99%)]\tLoss: 0.193259, Accuracy: 93.50\n",
      "\n",
      "Validation set: Average loss: 0.4164, Accuracy: 4330/5000 (86.00%)\n",
      "\n",
      "the time of this epoch:[21.428351879119873 s]\n",
      "Train Epoch: 38 [0/50000 (0%)]\tLoss: 0.164722, Accuracy: 94.14\n",
      "Train Epoch: 38 [1280/50000 (3%)]\tLoss: 0.222746, Accuracy: 93.75\n",
      "Train Epoch: 38 [2560/50000 (6%)]\tLoss: 0.183003, Accuracy: 93.75\n",
      "Train Epoch: 38 [3840/50000 (9%)]\tLoss: 0.236023, Accuracy: 91.41\n",
      "Train Epoch: 38 [5120/50000 (11%)]\tLoss: 0.181994, Accuracy: 95.31\n",
      "Train Epoch: 38 [6400/50000 (14%)]\tLoss: 0.131017, Accuracy: 95.31\n",
      "Train Epoch: 38 [7680/50000 (17%)]\tLoss: 0.183624, Accuracy: 92.19\n",
      "Train Epoch: 38 [8960/50000 (20%)]\tLoss: 0.227263, Accuracy: 90.62\n",
      "Train Epoch: 38 [10240/50000 (23%)]\tLoss: 0.152174, Accuracy: 94.92\n",
      "Train Epoch: 38 [11520/50000 (26%)]\tLoss: 0.204646, Accuracy: 91.41\n",
      "Train Epoch: 38 [12800/50000 (28%)]\tLoss: 0.192253, Accuracy: 93.36\n",
      "Train Epoch: 38 [14080/50000 (31%)]\tLoss: 0.199894, Accuracy: 91.02\n",
      "Train Epoch: 38 [15360/50000 (34%)]\tLoss: 0.258798, Accuracy: 90.23\n",
      "Train Epoch: 38 [16640/50000 (37%)]\tLoss: 0.154943, Accuracy: 95.31\n",
      "Train Epoch: 38 [17920/50000 (40%)]\tLoss: 0.238638, Accuracy: 92.19\n",
      "Train Epoch: 38 [19200/50000 (43%)]\tLoss: 0.134200, Accuracy: 95.31\n",
      "Train Epoch: 38 [20480/50000 (45%)]\tLoss: 0.228186, Accuracy: 92.97\n",
      "Train Epoch: 38 [21760/50000 (48%)]\tLoss: 0.166251, Accuracy: 94.53\n",
      "Train Epoch: 38 [23040/50000 (51%)]\tLoss: 0.206240, Accuracy: 92.19\n",
      "Train Epoch: 38 [24320/50000 (54%)]\tLoss: 0.142347, Accuracy: 96.09\n",
      "Train Epoch: 38 [25600/50000 (57%)]\tLoss: 0.131479, Accuracy: 95.70\n",
      "Train Epoch: 38 [26880/50000 (60%)]\tLoss: 0.137123, Accuracy: 94.14\n",
      "Train Epoch: 38 [28160/50000 (62%)]\tLoss: 0.210963, Accuracy: 92.97\n",
      "Train Epoch: 38 [29440/50000 (65%)]\tLoss: 0.175328, Accuracy: 94.53\n",
      "Train Epoch: 38 [30720/50000 (68%)]\tLoss: 0.147028, Accuracy: 94.14\n",
      "Train Epoch: 38 [32000/50000 (71%)]\tLoss: 0.212602, Accuracy: 93.36\n",
      "Train Epoch: 38 [33280/50000 (74%)]\tLoss: 0.239873, Accuracy: 90.23\n",
      "Train Epoch: 38 [34560/50000 (77%)]\tLoss: 0.163219, Accuracy: 94.53\n",
      "Train Epoch: 38 [35840/50000 (80%)]\tLoss: 0.322005, Accuracy: 87.11\n",
      "Train Epoch: 38 [37120/50000 (82%)]\tLoss: 0.175868, Accuracy: 93.36\n",
      "Train Epoch: 38 [38400/50000 (85%)]\tLoss: 0.204834, Accuracy: 92.58\n",
      "Train Epoch: 38 [39680/50000 (88%)]\tLoss: 0.250343, Accuracy: 90.62\n",
      "Train Epoch: 38 [40960/50000 (91%)]\tLoss: 0.220948, Accuracy: 91.02\n",
      "Train Epoch: 38 [42240/50000 (94%)]\tLoss: 0.236984, Accuracy: 92.58\n",
      "Train Epoch: 38 [43520/50000 (97%)]\tLoss: 0.187461, Accuracy: 93.36\n",
      "Train Epoch: 38 [35000/50000 (99%)]\tLoss: 0.189985, Accuracy: 93.50\n",
      "\n",
      "Validation set: Average loss: 0.3881, Accuracy: 4404/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.407182455062866 s]\n",
      "Train Epoch: 39 [0/50000 (0%)]\tLoss: 0.226939, Accuracy: 90.62\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 39 [1280/50000 (3%)]\tLoss: 0.232121, Accuracy: 91.41\n",
      "Train Epoch: 39 [2560/50000 (6%)]\tLoss: 0.184038, Accuracy: 92.97\n",
      "Train Epoch: 39 [3840/50000 (9%)]\tLoss: 0.198745, Accuracy: 94.92\n",
      "Train Epoch: 39 [5120/50000 (11%)]\tLoss: 0.126360, Accuracy: 95.31\n",
      "Train Epoch: 39 [6400/50000 (14%)]\tLoss: 0.176930, Accuracy: 92.97\n",
      "Train Epoch: 39 [7680/50000 (17%)]\tLoss: 0.169190, Accuracy: 94.92\n",
      "Train Epoch: 39 [8960/50000 (20%)]\tLoss: 0.143111, Accuracy: 94.14\n",
      "Train Epoch: 39 [10240/50000 (23%)]\tLoss: 0.193106, Accuracy: 92.97\n",
      "Train Epoch: 39 [11520/50000 (26%)]\tLoss: 0.245322, Accuracy: 89.84\n",
      "Train Epoch: 39 [12800/50000 (28%)]\tLoss: 0.142399, Accuracy: 94.92\n",
      "Train Epoch: 39 [14080/50000 (31%)]\tLoss: 0.279097, Accuracy: 89.45\n",
      "Train Epoch: 39 [15360/50000 (34%)]\tLoss: 0.171037, Accuracy: 92.97\n",
      "Train Epoch: 39 [16640/50000 (37%)]\tLoss: 0.187598, Accuracy: 92.97\n",
      "Train Epoch: 39 [17920/50000 (40%)]\tLoss: 0.230832, Accuracy: 91.02\n",
      "Train Epoch: 39 [19200/50000 (43%)]\tLoss: 0.239380, Accuracy: 90.62\n",
      "Train Epoch: 39 [20480/50000 (45%)]\tLoss: 0.217050, Accuracy: 93.75\n",
      "Train Epoch: 39 [21760/50000 (48%)]\tLoss: 0.150102, Accuracy: 95.31\n",
      "Train Epoch: 39 [23040/50000 (51%)]\tLoss: 0.230701, Accuracy: 91.41\n",
      "Train Epoch: 39 [24320/50000 (54%)]\tLoss: 0.106152, Accuracy: 96.48\n",
      "Train Epoch: 39 [25600/50000 (57%)]\tLoss: 0.230891, Accuracy: 92.58\n",
      "Train Epoch: 39 [26880/50000 (60%)]\tLoss: 0.209523, Accuracy: 91.80\n",
      "Train Epoch: 39 [28160/50000 (62%)]\tLoss: 0.201872, Accuracy: 92.19\n",
      "Train Epoch: 39 [29440/50000 (65%)]\tLoss: 0.194853, Accuracy: 93.36\n",
      "Train Epoch: 39 [30720/50000 (68%)]\tLoss: 0.156502, Accuracy: 94.14\n",
      "Train Epoch: 39 [32000/50000 (71%)]\tLoss: 0.214994, Accuracy: 93.36\n",
      "Train Epoch: 39 [33280/50000 (74%)]\tLoss: 0.194820, Accuracy: 92.97\n",
      "Train Epoch: 39 [34560/50000 (77%)]\tLoss: 0.216728, Accuracy: 91.80\n",
      "Train Epoch: 39 [35840/50000 (80%)]\tLoss: 0.169965, Accuracy: 93.75\n",
      "Train Epoch: 39 [37120/50000 (82%)]\tLoss: 0.137496, Accuracy: 93.75\n",
      "Train Epoch: 39 [38400/50000 (85%)]\tLoss: 0.223450, Accuracy: 91.41\n",
      "Train Epoch: 39 [39680/50000 (88%)]\tLoss: 0.196299, Accuracy: 93.75\n",
      "Train Epoch: 39 [40960/50000 (91%)]\tLoss: 0.211609, Accuracy: 93.36\n",
      "Train Epoch: 39 [42240/50000 (94%)]\tLoss: 0.279853, Accuracy: 89.45\n",
      "Train Epoch: 39 [43520/50000 (97%)]\tLoss: 0.215538, Accuracy: 92.97\n",
      "Train Epoch: 39 [35000/50000 (99%)]\tLoss: 0.318791, Accuracy: 88.50\n",
      "\n",
      "Validation set: Average loss: 0.4024, Accuracy: 4370/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.399800777435303 s]\n",
      "Train Epoch: 40 [0/50000 (0%)]\tLoss: 0.234778, Accuracy: 93.75\n",
      "Train Epoch: 40 [1280/50000 (3%)]\tLoss: 0.181183, Accuracy: 92.19\n",
      "Train Epoch: 40 [2560/50000 (6%)]\tLoss: 0.221581, Accuracy: 90.23\n",
      "Train Epoch: 40 [3840/50000 (9%)]\tLoss: 0.177986, Accuracy: 94.92\n",
      "Train Epoch: 40 [5120/50000 (11%)]\tLoss: 0.166713, Accuracy: 93.75\n",
      "Train Epoch: 40 [6400/50000 (14%)]\tLoss: 0.169016, Accuracy: 94.14\n",
      "Train Epoch: 40 [7680/50000 (17%)]\tLoss: 0.195921, Accuracy: 92.97\n",
      "Train Epoch: 40 [8960/50000 (20%)]\tLoss: 0.152427, Accuracy: 94.14\n",
      "Train Epoch: 40 [10240/50000 (23%)]\tLoss: 0.152673, Accuracy: 93.75\n",
      "Train Epoch: 40 [11520/50000 (26%)]\tLoss: 0.225436, Accuracy: 91.80\n",
      "Train Epoch: 40 [12800/50000 (28%)]\tLoss: 0.203894, Accuracy: 92.97\n",
      "Train Epoch: 40 [14080/50000 (31%)]\tLoss: 0.186516, Accuracy: 93.36\n",
      "Train Epoch: 40 [15360/50000 (34%)]\tLoss: 0.179245, Accuracy: 93.36\n",
      "Train Epoch: 40 [16640/50000 (37%)]\tLoss: 0.230401, Accuracy: 92.58\n",
      "Train Epoch: 40 [17920/50000 (40%)]\tLoss: 0.216238, Accuracy: 94.53\n",
      "Train Epoch: 40 [19200/50000 (43%)]\tLoss: 0.225597, Accuracy: 91.41\n",
      "Train Epoch: 40 [20480/50000 (45%)]\tLoss: 0.234418, Accuracy: 90.62\n",
      "Train Epoch: 40 [21760/50000 (48%)]\tLoss: 0.211646, Accuracy: 94.53\n",
      "Train Epoch: 40 [23040/50000 (51%)]\tLoss: 0.251541, Accuracy: 91.41\n",
      "Train Epoch: 40 [24320/50000 (54%)]\tLoss: 0.195223, Accuracy: 93.75\n",
      "Train Epoch: 40 [25600/50000 (57%)]\tLoss: 0.131942, Accuracy: 95.31\n",
      "Train Epoch: 40 [26880/50000 (60%)]\tLoss: 0.098372, Accuracy: 96.48\n",
      "Train Epoch: 40 [28160/50000 (62%)]\tLoss: 0.252509, Accuracy: 92.19\n",
      "Train Epoch: 40 [29440/50000 (65%)]\tLoss: 0.169774, Accuracy: 94.14\n",
      "Train Epoch: 40 [30720/50000 (68%)]\tLoss: 0.181529, Accuracy: 92.58\n",
      "Train Epoch: 40 [32000/50000 (71%)]\tLoss: 0.212372, Accuracy: 92.58\n",
      "Train Epoch: 40 [33280/50000 (74%)]\tLoss: 0.172518, Accuracy: 93.36\n",
      "Train Epoch: 40 [34560/50000 (77%)]\tLoss: 0.177786, Accuracy: 92.58\n",
      "Train Epoch: 40 [35840/50000 (80%)]\tLoss: 0.201026, Accuracy: 92.19\n",
      "Train Epoch: 40 [37120/50000 (82%)]\tLoss: 0.168261, Accuracy: 93.36\n",
      "Train Epoch: 40 [38400/50000 (85%)]\tLoss: 0.215462, Accuracy: 91.02\n",
      "Train Epoch: 40 [39680/50000 (88%)]\tLoss: 0.212045, Accuracy: 91.41\n",
      "Train Epoch: 40 [40960/50000 (91%)]\tLoss: 0.222011, Accuracy: 92.58\n",
      "Train Epoch: 40 [42240/50000 (94%)]\tLoss: 0.145322, Accuracy: 95.31\n",
      "Train Epoch: 40 [43520/50000 (97%)]\tLoss: 0.209975, Accuracy: 91.80\n",
      "Train Epoch: 40 [35000/50000 (99%)]\tLoss: 0.199985, Accuracy: 90.50\n",
      "\n",
      "Validation set: Average loss: 0.3924, Accuracy: 4382/5000 (87.00%)\n",
      "\n",
      "the time of this epoch:[21.397370100021362 s]\n",
      "Train Epoch: 41 [0/50000 (0%)]\tLoss: 0.207248, Accuracy: 92.19\n",
      "Train Epoch: 41 [1280/50000 (3%)]\tLoss: 0.190541, Accuracy: 92.97\n",
      "Train Epoch: 41 [2560/50000 (6%)]\tLoss: 0.164933, Accuracy: 94.14\n",
      "Train Epoch: 41 [3840/50000 (9%)]\tLoss: 0.103004, Accuracy: 96.88\n",
      "Train Epoch: 41 [5120/50000 (11%)]\tLoss: 0.154300, Accuracy: 94.53\n",
      "Train Epoch: 41 [6400/50000 (14%)]\tLoss: 0.161015, Accuracy: 95.31\n",
      "Train Epoch: 41 [7680/50000 (17%)]\tLoss: 0.141069, Accuracy: 93.75\n",
      "Train Epoch: 41 [8960/50000 (20%)]\tLoss: 0.179308, Accuracy: 94.14\n",
      "Train Epoch: 41 [10240/50000 (23%)]\tLoss: 0.175503, Accuracy: 94.53\n",
      "Train Epoch: 41 [11520/50000 (26%)]\tLoss: 0.190544, Accuracy: 93.75\n",
      "Train Epoch: 41 [12800/50000 (28%)]\tLoss: 0.140979, Accuracy: 96.09\n",
      "Train Epoch: 41 [14080/50000 (31%)]\tLoss: 0.157131, Accuracy: 93.75\n",
      "Train Epoch: 41 [15360/50000 (34%)]\tLoss: 0.132519, Accuracy: 96.09\n",
      "Train Epoch: 41 [16640/50000 (37%)]\tLoss: 0.161409, Accuracy: 93.36\n",
      "Train Epoch: 41 [17920/50000 (40%)]\tLoss: 0.127103, Accuracy: 95.31\n",
      "Train Epoch: 41 [19200/50000 (43%)]\tLoss: 0.210175, Accuracy: 92.58\n",
      "Train Epoch: 41 [20480/50000 (45%)]\tLoss: 0.223344, Accuracy: 92.97\n",
      "Train Epoch: 41 [21760/50000 (48%)]\tLoss: 0.135037, Accuracy: 94.53\n",
      "Train Epoch: 41 [23040/50000 (51%)]\tLoss: 0.160968, Accuracy: 94.92\n",
      "Train Epoch: 41 [24320/50000 (54%)]\tLoss: 0.109750, Accuracy: 96.88\n",
      "Train Epoch: 41 [25600/50000 (57%)]\tLoss: 0.173419, Accuracy: 94.14\n",
      "Train Epoch: 41 [26880/50000 (60%)]\tLoss: 0.208730, Accuracy: 92.19\n",
      "Train Epoch: 41 [28160/50000 (62%)]\tLoss: 0.134445, Accuracy: 94.53\n",
      "Train Epoch: 41 [29440/50000 (65%)]\tLoss: 0.166108, Accuracy: 94.92\n",
      "Train Epoch: 41 [30720/50000 (68%)]\tLoss: 0.104814, Accuracy: 95.70\n",
      "Train Epoch: 41 [32000/50000 (71%)]\tLoss: 0.151737, Accuracy: 94.53\n",
      "Train Epoch: 41 [33280/50000 (74%)]\tLoss: 0.220803, Accuracy: 94.53\n",
      "Train Epoch: 41 [34560/50000 (77%)]\tLoss: 0.126429, Accuracy: 94.53\n",
      "Train Epoch: 41 [35840/50000 (80%)]\tLoss: 0.151720, Accuracy: 93.75\n",
      "Train Epoch: 41 [37120/50000 (82%)]\tLoss: 0.128808, Accuracy: 96.09\n",
      "Train Epoch: 41 [38400/50000 (85%)]\tLoss: 0.207064, Accuracy: 92.97\n",
      "Train Epoch: 41 [39680/50000 (88%)]\tLoss: 0.136968, Accuracy: 95.31\n",
      "Train Epoch: 41 [40960/50000 (91%)]\tLoss: 0.096177, Accuracy: 96.09\n",
      "Train Epoch: 41 [42240/50000 (94%)]\tLoss: 0.158939, Accuracy: 93.36\n",
      "Train Epoch: 41 [43520/50000 (97%)]\tLoss: 0.175634, Accuracy: 93.36\n",
      "Train Epoch: 41 [35000/50000 (99%)]\tLoss: 0.172953, Accuracy: 95.50\n",
      "\n",
      "Validation set: Average loss: 0.3797, Accuracy: 4415/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.38840937614441 s]\n",
      "Train Epoch: 42 [0/50000 (0%)]\tLoss: 0.121620, Accuracy: 95.70\n",
      "Train Epoch: 42 [1280/50000 (3%)]\tLoss: 0.159341, Accuracy: 94.53\n",
      "Train Epoch: 42 [2560/50000 (6%)]\tLoss: 0.113199, Accuracy: 96.88\n",
      "Train Epoch: 42 [3840/50000 (9%)]\tLoss: 0.134014, Accuracy: 95.70\n",
      "Train Epoch: 42 [5120/50000 (11%)]\tLoss: 0.145202, Accuracy: 93.75\n",
      "Train Epoch: 42 [6400/50000 (14%)]\tLoss: 0.103184, Accuracy: 96.88\n",
      "Train Epoch: 42 [7680/50000 (17%)]\tLoss: 0.131435, Accuracy: 95.70\n",
      "Train Epoch: 42 [8960/50000 (20%)]\tLoss: 0.185363, Accuracy: 92.19\n",
      "Train Epoch: 42 [10240/50000 (23%)]\tLoss: 0.137060, Accuracy: 93.75\n",
      "Train Epoch: 42 [11520/50000 (26%)]\tLoss: 0.175533, Accuracy: 92.19\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 42 [12800/50000 (28%)]\tLoss: 0.148961, Accuracy: 94.53\n",
      "Train Epoch: 42 [14080/50000 (31%)]\tLoss: 0.127880, Accuracy: 94.92\n",
      "Train Epoch: 42 [15360/50000 (34%)]\tLoss: 0.136094, Accuracy: 94.92\n",
      "Train Epoch: 42 [16640/50000 (37%)]\tLoss: 0.087718, Accuracy: 97.27\n",
      "Train Epoch: 42 [17920/50000 (40%)]\tLoss: 0.111652, Accuracy: 95.31\n",
      "Train Epoch: 42 [19200/50000 (43%)]\tLoss: 0.138007, Accuracy: 95.31\n",
      "Train Epoch: 42 [20480/50000 (45%)]\tLoss: 0.142608, Accuracy: 95.31\n",
      "Train Epoch: 42 [21760/50000 (48%)]\tLoss: 0.208162, Accuracy: 91.41\n",
      "Train Epoch: 42 [23040/50000 (51%)]\tLoss: 0.145097, Accuracy: 93.75\n",
      "Train Epoch: 42 [24320/50000 (54%)]\tLoss: 0.167948, Accuracy: 94.53\n",
      "Train Epoch: 42 [25600/50000 (57%)]\tLoss: 0.190191, Accuracy: 94.14\n",
      "Train Epoch: 42 [26880/50000 (60%)]\tLoss: 0.140129, Accuracy: 95.70\n",
      "Train Epoch: 42 [28160/50000 (62%)]\tLoss: 0.125888, Accuracy: 95.31\n",
      "Train Epoch: 42 [29440/50000 (65%)]\tLoss: 0.136463, Accuracy: 92.97\n",
      "Train Epoch: 42 [30720/50000 (68%)]\tLoss: 0.142275, Accuracy: 94.53\n",
      "Train Epoch: 42 [32000/50000 (71%)]\tLoss: 0.111636, Accuracy: 94.92\n",
      "Train Epoch: 42 [33280/50000 (74%)]\tLoss: 0.126396, Accuracy: 96.09\n",
      "Train Epoch: 42 [34560/50000 (77%)]\tLoss: 0.140218, Accuracy: 95.31\n",
      "Train Epoch: 42 [35840/50000 (80%)]\tLoss: 0.192764, Accuracy: 93.75\n",
      "Train Epoch: 42 [37120/50000 (82%)]\tLoss: 0.152093, Accuracy: 95.31\n",
      "Train Epoch: 42 [38400/50000 (85%)]\tLoss: 0.144664, Accuracy: 96.09\n",
      "Train Epoch: 42 [39680/50000 (88%)]\tLoss: 0.118400, Accuracy: 95.70\n",
      "Train Epoch: 42 [40960/50000 (91%)]\tLoss: 0.123981, Accuracy: 95.31\n",
      "Train Epoch: 42 [42240/50000 (94%)]\tLoss: 0.130530, Accuracy: 95.70\n",
      "Train Epoch: 42 [43520/50000 (97%)]\tLoss: 0.104960, Accuracy: 95.70\n",
      "Train Epoch: 42 [35000/50000 (99%)]\tLoss: 0.229055, Accuracy: 92.00\n",
      "\n",
      "Validation set: Average loss: 0.3599, Accuracy: 4445/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.414539337158203 s]\n",
      "Train Epoch: 43 [0/50000 (0%)]\tLoss: 0.118527, Accuracy: 95.70\n",
      "Train Epoch: 43 [1280/50000 (3%)]\tLoss: 0.132176, Accuracy: 95.31\n",
      "Train Epoch: 43 [2560/50000 (6%)]\tLoss: 0.126459, Accuracy: 96.48\n",
      "Train Epoch: 43 [3840/50000 (9%)]\tLoss: 0.108429, Accuracy: 95.70\n",
      "Train Epoch: 43 [5120/50000 (11%)]\tLoss: 0.169999, Accuracy: 94.53\n",
      "Train Epoch: 43 [6400/50000 (14%)]\tLoss: 0.099085, Accuracy: 96.48\n",
      "Train Epoch: 43 [7680/50000 (17%)]\tLoss: 0.130713, Accuracy: 95.70\n",
      "Train Epoch: 43 [8960/50000 (20%)]\tLoss: 0.153388, Accuracy: 94.14\n",
      "Train Epoch: 43 [10240/50000 (23%)]\tLoss: 0.067897, Accuracy: 97.66\n",
      "Train Epoch: 43 [11520/50000 (26%)]\tLoss: 0.184574, Accuracy: 93.75\n",
      "Train Epoch: 43 [12800/50000 (28%)]\tLoss: 0.140445, Accuracy: 94.92\n",
      "Train Epoch: 43 [14080/50000 (31%)]\tLoss: 0.139867, Accuracy: 95.31\n",
      "Train Epoch: 43 [15360/50000 (34%)]\tLoss: 0.144739, Accuracy: 93.75\n",
      "Train Epoch: 43 [16640/50000 (37%)]\tLoss: 0.156964, Accuracy: 94.14\n",
      "Train Epoch: 43 [17920/50000 (40%)]\tLoss: 0.158781, Accuracy: 94.92\n",
      "Train Epoch: 43 [19200/50000 (43%)]\tLoss: 0.129429, Accuracy: 97.27\n",
      "Train Epoch: 43 [20480/50000 (45%)]\tLoss: 0.157439, Accuracy: 94.92\n",
      "Train Epoch: 43 [21760/50000 (48%)]\tLoss: 0.179699, Accuracy: 94.92\n",
      "Train Epoch: 43 [23040/50000 (51%)]\tLoss: 0.114398, Accuracy: 94.53\n",
      "Train Epoch: 43 [24320/50000 (54%)]\tLoss: 0.123451, Accuracy: 94.92\n",
      "Train Epoch: 43 [25600/50000 (57%)]\tLoss: 0.107356, Accuracy: 96.09\n",
      "Train Epoch: 43 [26880/50000 (60%)]\tLoss: 0.173990, Accuracy: 93.75\n",
      "Train Epoch: 43 [28160/50000 (62%)]\tLoss: 0.107729, Accuracy: 95.31\n",
      "Train Epoch: 43 [29440/50000 (65%)]\tLoss: 0.129273, Accuracy: 96.88\n",
      "Train Epoch: 43 [30720/50000 (68%)]\tLoss: 0.102396, Accuracy: 96.09\n",
      "Train Epoch: 43 [32000/50000 (71%)]\tLoss: 0.238659, Accuracy: 92.19\n",
      "Train Epoch: 43 [33280/50000 (74%)]\tLoss: 0.146158, Accuracy: 94.92\n",
      "Train Epoch: 43 [34560/50000 (77%)]\tLoss: 0.096891, Accuracy: 96.88\n",
      "Train Epoch: 43 [35840/50000 (80%)]\tLoss: 0.119538, Accuracy: 94.14\n",
      "Train Epoch: 43 [37120/50000 (82%)]\tLoss: 0.129216, Accuracy: 96.48\n",
      "Train Epoch: 43 [38400/50000 (85%)]\tLoss: 0.136414, Accuracy: 95.70\n",
      "Train Epoch: 43 [39680/50000 (88%)]\tLoss: 0.182276, Accuracy: 94.53\n",
      "Train Epoch: 43 [40960/50000 (91%)]\tLoss: 0.150508, Accuracy: 94.14\n",
      "Train Epoch: 43 [42240/50000 (94%)]\tLoss: 0.129423, Accuracy: 94.53\n",
      "Train Epoch: 43 [43520/50000 (97%)]\tLoss: 0.174288, Accuracy: 94.53\n",
      "Train Epoch: 43 [35000/50000 (99%)]\tLoss: 0.108187, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.3920, Accuracy: 4436/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.38102650642395 s]\n",
      "Train Epoch: 44 [0/50000 (0%)]\tLoss: 0.101924, Accuracy: 96.09\n",
      "Train Epoch: 44 [1280/50000 (3%)]\tLoss: 0.101868, Accuracy: 94.92\n",
      "Train Epoch: 44 [2560/50000 (6%)]\tLoss: 0.078222, Accuracy: 97.27\n",
      "Train Epoch: 44 [3840/50000 (9%)]\tLoss: 0.121124, Accuracy: 95.70\n",
      "Train Epoch: 44 [5120/50000 (11%)]\tLoss: 0.128047, Accuracy: 96.09\n",
      "Train Epoch: 44 [6400/50000 (14%)]\tLoss: 0.100911, Accuracy: 96.09\n",
      "Train Epoch: 44 [7680/50000 (17%)]\tLoss: 0.074300, Accuracy: 98.05\n",
      "Train Epoch: 44 [8960/50000 (20%)]\tLoss: 0.165216, Accuracy: 93.36\n",
      "Train Epoch: 44 [10240/50000 (23%)]\tLoss: 0.153341, Accuracy: 94.14\n",
      "Train Epoch: 44 [11520/50000 (26%)]\tLoss: 0.092965, Accuracy: 96.88\n",
      "Train Epoch: 44 [12800/50000 (28%)]\tLoss: 0.131313, Accuracy: 97.27\n",
      "Train Epoch: 44 [14080/50000 (31%)]\tLoss: 0.098309, Accuracy: 96.09\n",
      "Train Epoch: 44 [15360/50000 (34%)]\tLoss: 0.110633, Accuracy: 95.70\n",
      "Train Epoch: 44 [16640/50000 (37%)]\tLoss: 0.162827, Accuracy: 95.31\n",
      "Train Epoch: 44 [17920/50000 (40%)]\tLoss: 0.157608, Accuracy: 92.97\n",
      "Train Epoch: 44 [19200/50000 (43%)]\tLoss: 0.113632, Accuracy: 96.48\n",
      "Train Epoch: 44 [20480/50000 (45%)]\tLoss: 0.122660, Accuracy: 95.70\n",
      "Train Epoch: 44 [21760/50000 (48%)]\tLoss: 0.153543, Accuracy: 96.09\n",
      "Train Epoch: 44 [23040/50000 (51%)]\tLoss: 0.143993, Accuracy: 94.14\n",
      "Train Epoch: 44 [24320/50000 (54%)]\tLoss: 0.101342, Accuracy: 97.66\n",
      "Train Epoch: 44 [25600/50000 (57%)]\tLoss: 0.120325, Accuracy: 95.31\n",
      "Train Epoch: 44 [26880/50000 (60%)]\tLoss: 0.117917, Accuracy: 96.48\n",
      "Train Epoch: 44 [28160/50000 (62%)]\tLoss: 0.083343, Accuracy: 97.66\n",
      "Train Epoch: 44 [29440/50000 (65%)]\tLoss: 0.216848, Accuracy: 93.36\n",
      "Train Epoch: 44 [30720/50000 (68%)]\tLoss: 0.087284, Accuracy: 96.88\n",
      "Train Epoch: 44 [32000/50000 (71%)]\tLoss: 0.153167, Accuracy: 93.36\n",
      "Train Epoch: 44 [33280/50000 (74%)]\tLoss: 0.090077, Accuracy: 95.70\n",
      "Train Epoch: 44 [34560/50000 (77%)]\tLoss: 0.119047, Accuracy: 96.09\n",
      "Train Epoch: 44 [35840/50000 (80%)]\tLoss: 0.123125, Accuracy: 95.70\n",
      "Train Epoch: 44 [37120/50000 (82%)]\tLoss: 0.096937, Accuracy: 95.31\n",
      "Train Epoch: 44 [38400/50000 (85%)]\tLoss: 0.159376, Accuracy: 94.53\n",
      "Train Epoch: 44 [39680/50000 (88%)]\tLoss: 0.120672, Accuracy: 94.53\n",
      "Train Epoch: 44 [40960/50000 (91%)]\tLoss: 0.197387, Accuracy: 94.14\n",
      "Train Epoch: 44 [42240/50000 (94%)]\tLoss: 0.086592, Accuracy: 98.05\n",
      "Train Epoch: 44 [43520/50000 (97%)]\tLoss: 0.137560, Accuracy: 93.75\n",
      "Train Epoch: 44 [35000/50000 (99%)]\tLoss: 0.141511, Accuracy: 94.00\n",
      "\n",
      "Validation set: Average loss: 0.3928, Accuracy: 4408/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.371116161346436 s]\n",
      "Train Epoch: 45 [0/50000 (0%)]\tLoss: 0.108147, Accuracy: 97.66\n",
      "Train Epoch: 45 [1280/50000 (3%)]\tLoss: 0.122856, Accuracy: 95.31\n",
      "Train Epoch: 45 [2560/50000 (6%)]\tLoss: 0.160568, Accuracy: 94.14\n",
      "Train Epoch: 45 [3840/50000 (9%)]\tLoss: 0.115506, Accuracy: 96.88\n",
      "Train Epoch: 45 [5120/50000 (11%)]\tLoss: 0.169367, Accuracy: 93.36\n",
      "Train Epoch: 45 [6400/50000 (14%)]\tLoss: 0.154538, Accuracy: 94.14\n",
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      "Train Epoch: 45 [10240/50000 (23%)]\tLoss: 0.150408, Accuracy: 95.70\n",
      "Train Epoch: 45 [11520/50000 (26%)]\tLoss: 0.183924, Accuracy: 92.58\n",
      "Train Epoch: 45 [12800/50000 (28%)]\tLoss: 0.108059, Accuracy: 95.31\n",
      "Train Epoch: 45 [14080/50000 (31%)]\tLoss: 0.141839, Accuracy: 95.31\n",
      "Train Epoch: 45 [15360/50000 (34%)]\tLoss: 0.103640, Accuracy: 95.70\n",
      "Train Epoch: 45 [16640/50000 (37%)]\tLoss: 0.175637, Accuracy: 94.14\n",
      "Train Epoch: 45 [17920/50000 (40%)]\tLoss: 0.175208, Accuracy: 94.14\n",
      "Train Epoch: 45 [19200/50000 (43%)]\tLoss: 0.094696, Accuracy: 95.31\n",
      "Train Epoch: 45 [20480/50000 (45%)]\tLoss: 0.084641, Accuracy: 97.66\n",
      "Train Epoch: 45 [21760/50000 (48%)]\tLoss: 0.099478, Accuracy: 95.70\n",
      "Train Epoch: 45 [23040/50000 (51%)]\tLoss: 0.154462, Accuracy: 95.31\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 45 [24320/50000 (54%)]\tLoss: 0.142178, Accuracy: 93.36\n",
      "Train Epoch: 45 [25600/50000 (57%)]\tLoss: 0.109939, Accuracy: 96.48\n",
      "Train Epoch: 45 [26880/50000 (60%)]\tLoss: 0.109662, Accuracy: 96.48\n",
      "Train Epoch: 45 [28160/50000 (62%)]\tLoss: 0.174683, Accuracy: 94.14\n",
      "Train Epoch: 45 [29440/50000 (65%)]\tLoss: 0.115820, Accuracy: 96.48\n",
      "Train Epoch: 45 [30720/50000 (68%)]\tLoss: 0.180597, Accuracy: 91.80\n",
      "Train Epoch: 45 [32000/50000 (71%)]\tLoss: 0.153743, Accuracy: 92.19\n",
      "Train Epoch: 45 [33280/50000 (74%)]\tLoss: 0.115973, Accuracy: 96.88\n",
      "Train Epoch: 45 [34560/50000 (77%)]\tLoss: 0.126262, Accuracy: 96.09\n",
      "Train Epoch: 45 [35840/50000 (80%)]\tLoss: 0.081456, Accuracy: 97.66\n",
      "Train Epoch: 45 [37120/50000 (82%)]\tLoss: 0.097929, Accuracy: 96.48\n",
      "Train Epoch: 45 [38400/50000 (85%)]\tLoss: 0.083215, Accuracy: 97.66\n",
      "Train Epoch: 45 [39680/50000 (88%)]\tLoss: 0.156946, Accuracy: 93.75\n",
      "Train Epoch: 45 [40960/50000 (91%)]\tLoss: 0.125523, Accuracy: 96.09\n",
      "Train Epoch: 45 [42240/50000 (94%)]\tLoss: 0.149029, Accuracy: 94.92\n",
      "Train Epoch: 45 [43520/50000 (97%)]\tLoss: 0.117353, Accuracy: 96.48\n",
      "Train Epoch: 45 [35000/50000 (99%)]\tLoss: 0.093204, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.3919, Accuracy: 4435/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.36109209060669 s]\n",
      "Train Epoch: 46 [0/50000 (0%)]\tLoss: 0.098349, Accuracy: 96.48\n",
      "Train Epoch: 46 [1280/50000 (3%)]\tLoss: 0.104008, Accuracy: 96.48\n",
      "Train Epoch: 46 [2560/50000 (6%)]\tLoss: 0.191746, Accuracy: 94.53\n",
      "Train Epoch: 46 [3840/50000 (9%)]\tLoss: 0.119103, Accuracy: 97.27\n",
      "Train Epoch: 46 [5120/50000 (11%)]\tLoss: 0.133793, Accuracy: 93.75\n",
      "Train Epoch: 46 [6400/50000 (14%)]\tLoss: 0.075840, Accuracy: 97.27\n",
      "Train Epoch: 46 [7680/50000 (17%)]\tLoss: 0.123456, Accuracy: 96.09\n",
      "Train Epoch: 46 [8960/50000 (20%)]\tLoss: 0.075345, Accuracy: 96.88\n",
      "Train Epoch: 46 [10240/50000 (23%)]\tLoss: 0.092895, Accuracy: 95.31\n",
      "Train Epoch: 46 [11520/50000 (26%)]\tLoss: 0.100614, Accuracy: 96.88\n",
      "Train Epoch: 46 [12800/50000 (28%)]\tLoss: 0.135206, Accuracy: 95.31\n",
      "Train Epoch: 46 [14080/50000 (31%)]\tLoss: 0.106775, Accuracy: 95.70\n",
      "Train Epoch: 46 [15360/50000 (34%)]\tLoss: 0.090429, Accuracy: 97.66\n",
      "Train Epoch: 46 [16640/50000 (37%)]\tLoss: 0.066857, Accuracy: 98.05\n",
      "Train Epoch: 46 [17920/50000 (40%)]\tLoss: 0.183451, Accuracy: 93.36\n",
      "Train Epoch: 46 [19200/50000 (43%)]\tLoss: 0.123041, Accuracy: 96.09\n",
      "Train Epoch: 46 [20480/50000 (45%)]\tLoss: 0.160266, Accuracy: 94.53\n",
      "Train Epoch: 46 [21760/50000 (48%)]\tLoss: 0.107870, Accuracy: 95.70\n",
      "Train Epoch: 46 [23040/50000 (51%)]\tLoss: 0.201108, Accuracy: 94.14\n",
      "Train Epoch: 46 [24320/50000 (54%)]\tLoss: 0.134628, Accuracy: 94.53\n",
      "Train Epoch: 46 [25600/50000 (57%)]\tLoss: 0.116893, Accuracy: 95.70\n",
      "Train Epoch: 46 [26880/50000 (60%)]\tLoss: 0.158167, Accuracy: 95.70\n",
      "Train Epoch: 46 [28160/50000 (62%)]\tLoss: 0.156141, Accuracy: 93.75\n",
      "Train Epoch: 46 [29440/50000 (65%)]\tLoss: 0.169505, Accuracy: 93.36\n",
      "Train Epoch: 46 [30720/50000 (68%)]\tLoss: 0.080635, Accuracy: 98.05\n",
      "Train Epoch: 46 [32000/50000 (71%)]\tLoss: 0.178130, Accuracy: 92.97\n",
      "Train Epoch: 46 [33280/50000 (74%)]\tLoss: 0.132921, Accuracy: 94.53\n",
      "Train Epoch: 46 [34560/50000 (77%)]\tLoss: 0.136743, Accuracy: 94.92\n",
      "Train Epoch: 46 [35840/50000 (80%)]\tLoss: 0.158760, Accuracy: 93.36\n",
      "Train Epoch: 46 [37120/50000 (82%)]\tLoss: 0.120518, Accuracy: 95.70\n",
      "Train Epoch: 46 [38400/50000 (85%)]\tLoss: 0.113017, Accuracy: 96.88\n",
      "Train Epoch: 46 [39680/50000 (88%)]\tLoss: 0.122076, Accuracy: 95.70\n",
      "Train Epoch: 46 [40960/50000 (91%)]\tLoss: 0.127964, Accuracy: 94.92\n",
      "Train Epoch: 46 [42240/50000 (94%)]\tLoss: 0.156497, Accuracy: 93.36\n",
      "Train Epoch: 46 [43520/50000 (97%)]\tLoss: 0.158910, Accuracy: 92.97\n",
      "Train Epoch: 46 [35000/50000 (99%)]\tLoss: 0.110956, Accuracy: 95.50\n",
      "\n",
      "Validation set: Average loss: 0.4035, Accuracy: 4426/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.404359102249146 s]\n",
      "Train Epoch: 47 [0/50000 (0%)]\tLoss: 0.151001, Accuracy: 94.53\n",
      "Train Epoch: 47 [1280/50000 (3%)]\tLoss: 0.084326, Accuracy: 96.09\n",
      "Train Epoch: 47 [2560/50000 (6%)]\tLoss: 0.074649, Accuracy: 97.27\n",
      "Train Epoch: 47 [3840/50000 (9%)]\tLoss: 0.112200, Accuracy: 96.09\n",
      "Train Epoch: 47 [5120/50000 (11%)]\tLoss: 0.165901, Accuracy: 94.53\n",
      "Train Epoch: 47 [6400/50000 (14%)]\tLoss: 0.101783, Accuracy: 96.88\n",
      "Train Epoch: 47 [7680/50000 (17%)]\tLoss: 0.062336, Accuracy: 98.05\n",
      "Train Epoch: 47 [8960/50000 (20%)]\tLoss: 0.105855, Accuracy: 96.48\n",
      "Train Epoch: 47 [10240/50000 (23%)]\tLoss: 0.109562, Accuracy: 95.31\n",
      "Train Epoch: 47 [11520/50000 (26%)]\tLoss: 0.102472, Accuracy: 96.09\n",
      "Train Epoch: 47 [12800/50000 (28%)]\tLoss: 0.214931, Accuracy: 93.36\n",
      "Train Epoch: 47 [14080/50000 (31%)]\tLoss: 0.091480, Accuracy: 96.48\n",
      "Train Epoch: 47 [15360/50000 (34%)]\tLoss: 0.094350, Accuracy: 96.88\n",
      "Train Epoch: 47 [16640/50000 (37%)]\tLoss: 0.194118, Accuracy: 94.14\n",
      "Train Epoch: 47 [17920/50000 (40%)]\tLoss: 0.176317, Accuracy: 92.58\n",
      "Train Epoch: 47 [19200/50000 (43%)]\tLoss: 0.135232, Accuracy: 95.31\n",
      "Train Epoch: 47 [20480/50000 (45%)]\tLoss: 0.083541, Accuracy: 97.66\n",
      "Train Epoch: 47 [21760/50000 (48%)]\tLoss: 0.167478, Accuracy: 93.75\n",
      "Train Epoch: 47 [23040/50000 (51%)]\tLoss: 0.131181, Accuracy: 94.92\n",
      "Train Epoch: 47 [24320/50000 (54%)]\tLoss: 0.084681, Accuracy: 97.27\n",
      "Train Epoch: 47 [25600/50000 (57%)]\tLoss: 0.155857, Accuracy: 92.19\n",
      "Train Epoch: 47 [26880/50000 (60%)]\tLoss: 0.080381, Accuracy: 96.48\n",
      "Train Epoch: 47 [28160/50000 (62%)]\tLoss: 0.066553, Accuracy: 98.05\n",
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      "Train Epoch: 47 [30720/50000 (68%)]\tLoss: 0.120392, Accuracy: 95.31\n",
      "Train Epoch: 47 [32000/50000 (71%)]\tLoss: 0.120238, Accuracy: 94.92\n",
      "Train Epoch: 47 [33280/50000 (74%)]\tLoss: 0.165310, Accuracy: 94.14\n",
      "Train Epoch: 47 [34560/50000 (77%)]\tLoss: 0.200110, Accuracy: 92.97\n",
      "Train Epoch: 47 [35840/50000 (80%)]\tLoss: 0.126956, Accuracy: 96.09\n",
      "Train Epoch: 47 [37120/50000 (82%)]\tLoss: 0.134919, Accuracy: 94.92\n",
      "Train Epoch: 47 [38400/50000 (85%)]\tLoss: 0.052944, Accuracy: 98.44\n",
      "Train Epoch: 47 [39680/50000 (88%)]\tLoss: 0.088600, Accuracy: 95.70\n",
      "Train Epoch: 47 [40960/50000 (91%)]\tLoss: 0.091236, Accuracy: 96.09\n",
      "Train Epoch: 47 [42240/50000 (94%)]\tLoss: 0.106579, Accuracy: 95.31\n",
      "Train Epoch: 47 [43520/50000 (97%)]\tLoss: 0.147647, Accuracy: 94.53\n",
      "Train Epoch: 47 [35000/50000 (99%)]\tLoss: 0.091072, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.3835, Accuracy: 4426/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.447504997253418 s]\n",
      "Train Epoch: 48 [0/50000 (0%)]\tLoss: 0.120362, Accuracy: 95.70\n",
      "Train Epoch: 48 [1280/50000 (3%)]\tLoss: 0.157651, Accuracy: 94.53\n",
      "Train Epoch: 48 [2560/50000 (6%)]\tLoss: 0.106136, Accuracy: 96.88\n",
      "Train Epoch: 48 [3840/50000 (9%)]\tLoss: 0.115121, Accuracy: 97.27\n",
      "Train Epoch: 48 [5120/50000 (11%)]\tLoss: 0.072705, Accuracy: 96.88\n",
      "Train Epoch: 48 [6400/50000 (14%)]\tLoss: 0.162741, Accuracy: 95.31\n",
      "Train Epoch: 48 [7680/50000 (17%)]\tLoss: 0.132788, Accuracy: 95.31\n",
      "Train Epoch: 48 [8960/50000 (20%)]\tLoss: 0.152198, Accuracy: 95.31\n",
      "Train Epoch: 48 [10240/50000 (23%)]\tLoss: 0.074628, Accuracy: 97.66\n",
      "Train Epoch: 48 [11520/50000 (26%)]\tLoss: 0.117745, Accuracy: 95.31\n",
      "Train Epoch: 48 [12800/50000 (28%)]\tLoss: 0.173814, Accuracy: 94.14\n",
      "Train Epoch: 48 [14080/50000 (31%)]\tLoss: 0.168831, Accuracy: 94.53\n",
      "Train Epoch: 48 [15360/50000 (34%)]\tLoss: 0.136620, Accuracy: 94.14\n",
      "Train Epoch: 48 [16640/50000 (37%)]\tLoss: 0.139889, Accuracy: 96.09\n",
      "Train Epoch: 48 [17920/50000 (40%)]\tLoss: 0.134254, Accuracy: 94.53\n",
      "Train Epoch: 48 [19200/50000 (43%)]\tLoss: 0.144884, Accuracy: 95.31\n",
      "Train Epoch: 48 [20480/50000 (45%)]\tLoss: 0.142822, Accuracy: 94.14\n",
      "Train Epoch: 48 [21760/50000 (48%)]\tLoss: 0.067821, Accuracy: 97.66\n",
      "Train Epoch: 48 [23040/50000 (51%)]\tLoss: 0.108590, Accuracy: 96.88\n",
      "Train Epoch: 48 [24320/50000 (54%)]\tLoss: 0.113440, Accuracy: 95.31\n",
      "Train Epoch: 48 [25600/50000 (57%)]\tLoss: 0.097701, Accuracy: 95.70\n",
      "Train Epoch: 48 [26880/50000 (60%)]\tLoss: 0.099847, Accuracy: 97.27\n",
      "Train Epoch: 48 [28160/50000 (62%)]\tLoss: 0.108097, Accuracy: 97.27\n",
      "Train Epoch: 48 [29440/50000 (65%)]\tLoss: 0.138070, Accuracy: 94.53\n",
      "Train Epoch: 48 [30720/50000 (68%)]\tLoss: 0.109490, Accuracy: 96.88\n",
      "Train Epoch: 48 [32000/50000 (71%)]\tLoss: 0.132423, Accuracy: 95.31\n",
      "Train Epoch: 48 [33280/50000 (74%)]\tLoss: 0.070957, Accuracy: 98.05\n",
      "Train Epoch: 48 [34560/50000 (77%)]\tLoss: 0.154388, Accuracy: 94.53\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 48 [35840/50000 (80%)]\tLoss: 0.132785, Accuracy: 96.88\n",
      "Train Epoch: 48 [37120/50000 (82%)]\tLoss: 0.079143, Accuracy: 97.66\n",
      "Train Epoch: 48 [38400/50000 (85%)]\tLoss: 0.107186, Accuracy: 95.70\n",
      "Train Epoch: 48 [39680/50000 (88%)]\tLoss: 0.150653, Accuracy: 94.92\n",
      "Train Epoch: 48 [40960/50000 (91%)]\tLoss: 0.168616, Accuracy: 93.75\n",
      "Train Epoch: 48 [42240/50000 (94%)]\tLoss: 0.128151, Accuracy: 96.09\n",
      "Train Epoch: 48 [43520/50000 (97%)]\tLoss: 0.111227, Accuracy: 96.48\n",
      "Train Epoch: 48 [35000/50000 (99%)]\tLoss: 0.124781, Accuracy: 95.50\n",
      "\n",
      "Validation set: Average loss: 0.3922, Accuracy: 4421/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.443223476409912 s]\n",
      "Train Epoch: 49 [0/50000 (0%)]\tLoss: 0.147933, Accuracy: 95.31\n",
      "Train Epoch: 49 [1280/50000 (3%)]\tLoss: 0.164236, Accuracy: 92.97\n",
      "Train Epoch: 49 [2560/50000 (6%)]\tLoss: 0.102138, Accuracy: 95.70\n",
      "Train Epoch: 49 [3840/50000 (9%)]\tLoss: 0.152885, Accuracy: 94.53\n",
      "Train Epoch: 49 [5120/50000 (11%)]\tLoss: 0.110285, Accuracy: 95.70\n",
      "Train Epoch: 49 [6400/50000 (14%)]\tLoss: 0.156782, Accuracy: 92.97\n",
      "Train Epoch: 49 [7680/50000 (17%)]\tLoss: 0.088748, Accuracy: 97.27\n",
      "Train Epoch: 49 [8960/50000 (20%)]\tLoss: 0.066379, Accuracy: 97.66\n",
      "Train Epoch: 49 [10240/50000 (23%)]\tLoss: 0.123487, Accuracy: 96.09\n",
      "Train Epoch: 49 [11520/50000 (26%)]\tLoss: 0.049236, Accuracy: 98.83\n",
      "Train Epoch: 49 [12800/50000 (28%)]\tLoss: 0.073470, Accuracy: 98.44\n",
      "Train Epoch: 49 [14080/50000 (31%)]\tLoss: 0.071385, Accuracy: 97.27\n",
      "Train Epoch: 49 [15360/50000 (34%)]\tLoss: 0.084720, Accuracy: 97.27\n",
      "Train Epoch: 49 [16640/50000 (37%)]\tLoss: 0.174837, Accuracy: 94.14\n",
      "Train Epoch: 49 [17920/50000 (40%)]\tLoss: 0.142539, Accuracy: 95.31\n",
      "Train Epoch: 49 [19200/50000 (43%)]\tLoss: 0.098761, Accuracy: 96.88\n",
      "Train Epoch: 49 [20480/50000 (45%)]\tLoss: 0.144072, Accuracy: 94.92\n",
      "Train Epoch: 49 [21760/50000 (48%)]\tLoss: 0.080625, Accuracy: 96.88\n",
      "Train Epoch: 49 [23040/50000 (51%)]\tLoss: 0.089537, Accuracy: 96.09\n",
      "Train Epoch: 49 [24320/50000 (54%)]\tLoss: 0.118083, Accuracy: 95.70\n",
      "Train Epoch: 49 [25600/50000 (57%)]\tLoss: 0.124098, Accuracy: 94.92\n",
      "Train Epoch: 49 [26880/50000 (60%)]\tLoss: 0.133837, Accuracy: 95.31\n",
      "Train Epoch: 49 [28160/50000 (62%)]\tLoss: 0.192399, Accuracy: 93.36\n",
      "Train Epoch: 49 [29440/50000 (65%)]\tLoss: 0.095767, Accuracy: 96.09\n",
      "Train Epoch: 49 [30720/50000 (68%)]\tLoss: 0.119821, Accuracy: 96.09\n",
      "Train Epoch: 49 [32000/50000 (71%)]\tLoss: 0.093338, Accuracy: 96.48\n",
      "Train Epoch: 49 [33280/50000 (74%)]\tLoss: 0.065434, Accuracy: 98.83\n",
      "Train Epoch: 49 [34560/50000 (77%)]\tLoss: 0.092635, Accuracy: 96.48\n",
      "Train Epoch: 49 [35840/50000 (80%)]\tLoss: 0.087002, Accuracy: 97.66\n",
      "Train Epoch: 49 [37120/50000 (82%)]\tLoss: 0.164968, Accuracy: 96.09\n",
      "Train Epoch: 49 [38400/50000 (85%)]\tLoss: 0.101151, Accuracy: 95.31\n",
      "Train Epoch: 49 [39680/50000 (88%)]\tLoss: 0.145688, Accuracy: 94.53\n",
      "Train Epoch: 49 [40960/50000 (91%)]\tLoss: 0.152714, Accuracy: 94.92\n",
      "Train Epoch: 49 [42240/50000 (94%)]\tLoss: 0.091814, Accuracy: 96.88\n",
      "Train Epoch: 49 [43520/50000 (97%)]\tLoss: 0.130631, Accuracy: 95.31\n",
      "Train Epoch: 49 [35000/50000 (99%)]\tLoss: 0.235178, Accuracy: 93.00\n",
      "\n",
      "Validation set: Average loss: 0.4318, Accuracy: 4406/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.4678897857666 s]\n",
      "Train Epoch: 50 [0/50000 (0%)]\tLoss: 0.105862, Accuracy: 96.09\n",
      "Train Epoch: 50 [1280/50000 (3%)]\tLoss: 0.116654, Accuracy: 96.09\n",
      "Train Epoch: 50 [2560/50000 (6%)]\tLoss: 0.082687, Accuracy: 96.48\n",
      "Train Epoch: 50 [3840/50000 (9%)]\tLoss: 0.136368, Accuracy: 95.31\n",
      "Train Epoch: 50 [5120/50000 (11%)]\tLoss: 0.085484, Accuracy: 96.88\n",
      "Train Epoch: 50 [6400/50000 (14%)]\tLoss: 0.148994, Accuracy: 95.31\n",
      "Train Epoch: 50 [7680/50000 (17%)]\tLoss: 0.131816, Accuracy: 95.70\n",
      "Train Epoch: 50 [8960/50000 (20%)]\tLoss: 0.143649, Accuracy: 95.31\n",
      "Train Epoch: 50 [10240/50000 (23%)]\tLoss: 0.098693, Accuracy: 96.88\n",
      "Train Epoch: 50 [11520/50000 (26%)]\tLoss: 0.137906, Accuracy: 95.31\n",
      "Train Epoch: 50 [12800/50000 (28%)]\tLoss: 0.074400, Accuracy: 97.27\n",
      "Train Epoch: 50 [14080/50000 (31%)]\tLoss: 0.089143, Accuracy: 97.27\n",
      "Train Epoch: 50 [15360/50000 (34%)]\tLoss: 0.083279, Accuracy: 96.88\n",
      "Train Epoch: 50 [16640/50000 (37%)]\tLoss: 0.073672, Accuracy: 97.27\n",
      "Train Epoch: 50 [17920/50000 (40%)]\tLoss: 0.113107, Accuracy: 96.48\n",
      "Train Epoch: 50 [19200/50000 (43%)]\tLoss: 0.150432, Accuracy: 95.31\n",
      "Train Epoch: 50 [20480/50000 (45%)]\tLoss: 0.108134, Accuracy: 94.92\n",
      "Train Epoch: 50 [21760/50000 (48%)]\tLoss: 0.120692, Accuracy: 96.09\n",
      "Train Epoch: 50 [23040/50000 (51%)]\tLoss: 0.156296, Accuracy: 94.53\n",
      "Train Epoch: 50 [24320/50000 (54%)]\tLoss: 0.132286, Accuracy: 94.53\n",
      "Train Epoch: 50 [25600/50000 (57%)]\tLoss: 0.149324, Accuracy: 95.70\n",
      "Train Epoch: 50 [26880/50000 (60%)]\tLoss: 0.136467, Accuracy: 95.31\n",
      "Train Epoch: 50 [28160/50000 (62%)]\tLoss: 0.123916, Accuracy: 95.31\n",
      "Train Epoch: 50 [29440/50000 (65%)]\tLoss: 0.068599, Accuracy: 98.44\n",
      "Train Epoch: 50 [30720/50000 (68%)]\tLoss: 0.104069, Accuracy: 97.27\n",
      "Train Epoch: 50 [32000/50000 (71%)]\tLoss: 0.130163, Accuracy: 94.92\n",
      "Train Epoch: 50 [33280/50000 (74%)]\tLoss: 0.099473, Accuracy: 97.27\n",
      "Train Epoch: 50 [34560/50000 (77%)]\tLoss: 0.139489, Accuracy: 96.09\n",
      "Train Epoch: 50 [35840/50000 (80%)]\tLoss: 0.114326, Accuracy: 96.48\n",
      "Train Epoch: 50 [37120/50000 (82%)]\tLoss: 0.117614, Accuracy: 95.31\n",
      "Train Epoch: 50 [38400/50000 (85%)]\tLoss: 0.100676, Accuracy: 97.66\n",
      "Train Epoch: 50 [39680/50000 (88%)]\tLoss: 0.109152, Accuracy: 96.09\n",
      "Train Epoch: 50 [40960/50000 (91%)]\tLoss: 0.133096, Accuracy: 96.09\n",
      "Train Epoch: 50 [42240/50000 (94%)]\tLoss: 0.112577, Accuracy: 96.09\n",
      "Train Epoch: 50 [43520/50000 (97%)]\tLoss: 0.126826, Accuracy: 96.48\n",
      "Train Epoch: 50 [35000/50000 (99%)]\tLoss: 0.131734, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.3911, Accuracy: 4448/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.397897243499756 s]\n",
      "Train Epoch: 51 [0/50000 (0%)]\tLoss: 0.110695, Accuracy: 96.48\n",
      "Train Epoch: 51 [1280/50000 (3%)]\tLoss: 0.170413, Accuracy: 93.75\n",
      "Train Epoch: 51 [2560/50000 (6%)]\tLoss: 0.124850, Accuracy: 96.09\n",
      "Train Epoch: 51 [3840/50000 (9%)]\tLoss: 0.116007, Accuracy: 96.48\n",
      "Train Epoch: 51 [5120/50000 (11%)]\tLoss: 0.065784, Accuracy: 97.66\n",
      "Train Epoch: 51 [6400/50000 (14%)]\tLoss: 0.133498, Accuracy: 94.92\n",
      "Train Epoch: 51 [7680/50000 (17%)]\tLoss: 0.143151, Accuracy: 94.92\n",
      "Train Epoch: 51 [8960/50000 (20%)]\tLoss: 0.111293, Accuracy: 96.48\n",
      "Train Epoch: 51 [10240/50000 (23%)]\tLoss: 0.077401, Accuracy: 96.88\n",
      "Train Epoch: 51 [11520/50000 (26%)]\tLoss: 0.052374, Accuracy: 98.83\n",
      "Train Epoch: 51 [12800/50000 (28%)]\tLoss: 0.106292, Accuracy: 95.31\n",
      "Train Epoch: 51 [14080/50000 (31%)]\tLoss: 0.100110, Accuracy: 96.88\n",
      "Train Epoch: 51 [15360/50000 (34%)]\tLoss: 0.144777, Accuracy: 94.92\n",
      "Train Epoch: 51 [16640/50000 (37%)]\tLoss: 0.129119, Accuracy: 95.31\n",
      "Train Epoch: 51 [17920/50000 (40%)]\tLoss: 0.129658, Accuracy: 96.09\n",
      "Train Epoch: 51 [19200/50000 (43%)]\tLoss: 0.202153, Accuracy: 93.75\n",
      "Train Epoch: 51 [20480/50000 (45%)]\tLoss: 0.142560, Accuracy: 96.09\n",
      "Train Epoch: 51 [21760/50000 (48%)]\tLoss: 0.091811, Accuracy: 97.27\n",
      "Train Epoch: 51 [23040/50000 (51%)]\tLoss: 0.111114, Accuracy: 95.70\n",
      "Train Epoch: 51 [24320/50000 (54%)]\tLoss: 0.115324, Accuracy: 93.75\n",
      "Train Epoch: 51 [25600/50000 (57%)]\tLoss: 0.106301, Accuracy: 96.09\n",
      "Train Epoch: 51 [26880/50000 (60%)]\tLoss: 0.123452, Accuracy: 94.92\n",
      "Train Epoch: 51 [28160/50000 (62%)]\tLoss: 0.070148, Accuracy: 98.05\n",
      "Train Epoch: 51 [29440/50000 (65%)]\tLoss: 0.072683, Accuracy: 96.88\n",
      "Train Epoch: 51 [30720/50000 (68%)]\tLoss: 0.147906, Accuracy: 94.92\n",
      "Train Epoch: 51 [32000/50000 (71%)]\tLoss: 0.100705, Accuracy: 96.48\n",
      "Train Epoch: 51 [33280/50000 (74%)]\tLoss: 0.127703, Accuracy: 97.27\n",
      "Train Epoch: 51 [34560/50000 (77%)]\tLoss: 0.188113, Accuracy: 94.92\n",
      "Train Epoch: 51 [35840/50000 (80%)]\tLoss: 0.138970, Accuracy: 95.70\n",
      "Train Epoch: 51 [37120/50000 (82%)]\tLoss: 0.100356, Accuracy: 96.09\n",
      "Train Epoch: 51 [38400/50000 (85%)]\tLoss: 0.152226, Accuracy: 94.53\n",
      "Train Epoch: 51 [39680/50000 (88%)]\tLoss: 0.080096, Accuracy: 96.48\n",
      "Train Epoch: 51 [40960/50000 (91%)]\tLoss: 0.106734, Accuracy: 96.48\n",
      "Train Epoch: 51 [42240/50000 (94%)]\tLoss: 0.106638, Accuracy: 96.09\n",
      "Train Epoch: 51 [43520/50000 (97%)]\tLoss: 0.125127, Accuracy: 95.70\n",
      "Train Epoch: 51 [35000/50000 (99%)]\tLoss: 0.092673, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.4359, Accuracy: 4413/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.415422201156616 s]\n",
      "Train Epoch: 52 [0/50000 (0%)]\tLoss: 0.102119, Accuracy: 96.88\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 52 [1280/50000 (3%)]\tLoss: 0.104939, Accuracy: 95.70\n",
      "Train Epoch: 52 [2560/50000 (6%)]\tLoss: 0.131971, Accuracy: 96.09\n",
      "Train Epoch: 52 [3840/50000 (9%)]\tLoss: 0.115354, Accuracy: 95.70\n",
      "Train Epoch: 52 [5120/50000 (11%)]\tLoss: 0.104603, Accuracy: 96.48\n",
      "Train Epoch: 52 [6400/50000 (14%)]\tLoss: 0.129875, Accuracy: 93.75\n",
      "Train Epoch: 52 [7680/50000 (17%)]\tLoss: 0.060986, Accuracy: 97.27\n",
      "Train Epoch: 52 [8960/50000 (20%)]\tLoss: 0.102479, Accuracy: 96.09\n",
      "Train Epoch: 52 [10240/50000 (23%)]\tLoss: 0.119257, Accuracy: 94.92\n",
      "Train Epoch: 52 [11520/50000 (26%)]\tLoss: 0.127732, Accuracy: 96.09\n",
      "Train Epoch: 52 [12800/50000 (28%)]\tLoss: 0.115556, Accuracy: 94.92\n",
      "Train Epoch: 52 [14080/50000 (31%)]\tLoss: 0.157308, Accuracy: 95.70\n",
      "Train Epoch: 52 [15360/50000 (34%)]\tLoss: 0.139462, Accuracy: 94.14\n",
      "Train Epoch: 52 [16640/50000 (37%)]\tLoss: 0.118838, Accuracy: 96.09\n",
      "Train Epoch: 52 [17920/50000 (40%)]\tLoss: 0.135043, Accuracy: 94.92\n",
      "Train Epoch: 52 [19200/50000 (43%)]\tLoss: 0.112994, Accuracy: 96.48\n",
      "Train Epoch: 52 [20480/50000 (45%)]\tLoss: 0.187658, Accuracy: 93.75\n",
      "Train Epoch: 52 [21760/50000 (48%)]\tLoss: 0.161026, Accuracy: 92.97\n",
      "Train Epoch: 52 [23040/50000 (51%)]\tLoss: 0.101117, Accuracy: 95.70\n",
      "Train Epoch: 52 [24320/50000 (54%)]\tLoss: 0.120902, Accuracy: 95.31\n",
      "Train Epoch: 52 [25600/50000 (57%)]\tLoss: 0.083736, Accuracy: 96.88\n",
      "Train Epoch: 52 [26880/50000 (60%)]\tLoss: 0.086718, Accuracy: 96.88\n",
      "Train Epoch: 52 [28160/50000 (62%)]\tLoss: 0.093266, Accuracy: 96.48\n",
      "Train Epoch: 52 [29440/50000 (65%)]\tLoss: 0.095820, Accuracy: 96.48\n",
      "Train Epoch: 52 [30720/50000 (68%)]\tLoss: 0.146115, Accuracy: 94.92\n",
      "Train Epoch: 52 [32000/50000 (71%)]\tLoss: 0.069888, Accuracy: 97.66\n",
      "Train Epoch: 52 [33280/50000 (74%)]\tLoss: 0.119378, Accuracy: 96.48\n",
      "Train Epoch: 52 [34560/50000 (77%)]\tLoss: 0.145953, Accuracy: 94.92\n",
      "Train Epoch: 52 [35840/50000 (80%)]\tLoss: 0.084210, Accuracy: 96.48\n",
      "Train Epoch: 52 [37120/50000 (82%)]\tLoss: 0.181598, Accuracy: 92.97\n",
      "Train Epoch: 52 [38400/50000 (85%)]\tLoss: 0.068297, Accuracy: 98.44\n",
      "Train Epoch: 52 [39680/50000 (88%)]\tLoss: 0.123174, Accuracy: 96.09\n",
      "Train Epoch: 52 [40960/50000 (91%)]\tLoss: 0.117375, Accuracy: 96.09\n",
      "Train Epoch: 52 [42240/50000 (94%)]\tLoss: 0.086546, Accuracy: 96.48\n",
      "Train Epoch: 52 [43520/50000 (97%)]\tLoss: 0.108826, Accuracy: 95.70\n",
      "Train Epoch: 52 [35000/50000 (99%)]\tLoss: 0.104293, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.4143, Accuracy: 4443/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.429389476776123 s]\n",
      "Train Epoch: 53 [0/50000 (0%)]\tLoss: 0.097052, Accuracy: 96.88\n",
      "Train Epoch: 53 [1280/50000 (3%)]\tLoss: 0.158829, Accuracy: 95.31\n",
      "Train Epoch: 53 [2560/50000 (6%)]\tLoss: 0.091331, Accuracy: 97.27\n",
      "Train Epoch: 53 [3840/50000 (9%)]\tLoss: 0.116438, Accuracy: 96.48\n",
      "Train Epoch: 53 [5120/50000 (11%)]\tLoss: 0.064823, Accuracy: 97.66\n",
      "Train Epoch: 53 [6400/50000 (14%)]\tLoss: 0.097125, Accuracy: 96.48\n",
      "Train Epoch: 53 [7680/50000 (17%)]\tLoss: 0.090297, Accuracy: 95.70\n",
      "Train Epoch: 53 [8960/50000 (20%)]\tLoss: 0.144778, Accuracy: 94.92\n",
      "Train Epoch: 53 [10240/50000 (23%)]\tLoss: 0.118754, Accuracy: 96.48\n",
      "Train Epoch: 53 [11520/50000 (26%)]\tLoss: 0.078089, Accuracy: 96.88\n",
      "Train Epoch: 53 [12800/50000 (28%)]\tLoss: 0.095687, Accuracy: 96.48\n",
      "Train Epoch: 53 [14080/50000 (31%)]\tLoss: 0.105775, Accuracy: 96.48\n",
      "Train Epoch: 53 [15360/50000 (34%)]\tLoss: 0.073415, Accuracy: 98.44\n",
      "Train Epoch: 53 [16640/50000 (37%)]\tLoss: 0.070166, Accuracy: 97.66\n",
      "Train Epoch: 53 [17920/50000 (40%)]\tLoss: 0.091951, Accuracy: 97.66\n",
      "Train Epoch: 53 [19200/50000 (43%)]\tLoss: 0.096093, Accuracy: 96.88\n",
      "Train Epoch: 53 [20480/50000 (45%)]\tLoss: 0.066721, Accuracy: 97.27\n",
      "Train Epoch: 53 [21760/50000 (48%)]\tLoss: 0.095781, Accuracy: 95.70\n",
      "Train Epoch: 53 [23040/50000 (51%)]\tLoss: 0.133384, Accuracy: 94.14\n",
      "Train Epoch: 53 [24320/50000 (54%)]\tLoss: 0.137521, Accuracy: 94.53\n",
      "Train Epoch: 53 [25600/50000 (57%)]\tLoss: 0.060164, Accuracy: 98.44\n",
      "Train Epoch: 53 [26880/50000 (60%)]\tLoss: 0.070690, Accuracy: 97.66\n",
      "Train Epoch: 53 [28160/50000 (62%)]\tLoss: 0.140402, Accuracy: 94.53\n",
      "Train Epoch: 53 [29440/50000 (65%)]\tLoss: 0.118057, Accuracy: 95.70\n",
      "Train Epoch: 53 [30720/50000 (68%)]\tLoss: 0.118895, Accuracy: 95.31\n",
      "Train Epoch: 53 [32000/50000 (71%)]\tLoss: 0.167037, Accuracy: 92.97\n",
      "Train Epoch: 53 [33280/50000 (74%)]\tLoss: 0.115937, Accuracy: 95.70\n",
      "Train Epoch: 53 [34560/50000 (77%)]\tLoss: 0.100863, Accuracy: 96.48\n",
      "Train Epoch: 53 [35840/50000 (80%)]\tLoss: 0.127379, Accuracy: 95.31\n",
      "Train Epoch: 53 [37120/50000 (82%)]\tLoss: 0.141995, Accuracy: 94.92\n",
      "Train Epoch: 53 [38400/50000 (85%)]\tLoss: 0.089392, Accuracy: 94.92\n",
      "Train Epoch: 53 [39680/50000 (88%)]\tLoss: 0.114071, Accuracy: 96.48\n",
      "Train Epoch: 53 [40960/50000 (91%)]\tLoss: 0.072310, Accuracy: 96.88\n",
      "Train Epoch: 53 [42240/50000 (94%)]\tLoss: 0.109157, Accuracy: 95.70\n",
      "Train Epoch: 53 [43520/50000 (97%)]\tLoss: 0.109904, Accuracy: 96.09\n",
      "Train Epoch: 53 [35000/50000 (99%)]\tLoss: 0.102580, Accuracy: 96.50\n",
      "\n",
      "Validation set: Average loss: 0.4336, Accuracy: 4425/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.43093776702881 s]\n",
      "Train Epoch: 54 [0/50000 (0%)]\tLoss: 0.087402, Accuracy: 97.27\n",
      "Train Epoch: 54 [1280/50000 (3%)]\tLoss: 0.089075, Accuracy: 96.48\n",
      "Train Epoch: 54 [2560/50000 (6%)]\tLoss: 0.111135, Accuracy: 96.48\n",
      "Train Epoch: 54 [3840/50000 (9%)]\tLoss: 0.089366, Accuracy: 97.27\n",
      "Train Epoch: 54 [5120/50000 (11%)]\tLoss: 0.074344, Accuracy: 97.66\n",
      "Train Epoch: 54 [6400/50000 (14%)]\tLoss: 0.095972, Accuracy: 96.48\n",
      "Train Epoch: 54 [7680/50000 (17%)]\tLoss: 0.133957, Accuracy: 94.53\n",
      "Train Epoch: 54 [8960/50000 (20%)]\tLoss: 0.091842, Accuracy: 96.88\n",
      "Train Epoch: 54 [10240/50000 (23%)]\tLoss: 0.110287, Accuracy: 95.31\n",
      "Train Epoch: 54 [11520/50000 (26%)]\tLoss: 0.083585, Accuracy: 96.48\n",
      "Train Epoch: 54 [12800/50000 (28%)]\tLoss: 0.134560, Accuracy: 94.92\n",
      "Train Epoch: 54 [14080/50000 (31%)]\tLoss: 0.078855, Accuracy: 97.66\n",
      "Train Epoch: 54 [15360/50000 (34%)]\tLoss: 0.127370, Accuracy: 95.31\n",
      "Train Epoch: 54 [16640/50000 (37%)]\tLoss: 0.097292, Accuracy: 96.88\n",
      "Train Epoch: 54 [17920/50000 (40%)]\tLoss: 0.061935, Accuracy: 97.27\n",
      "Train Epoch: 54 [19200/50000 (43%)]\tLoss: 0.073693, Accuracy: 98.05\n",
      "Train Epoch: 54 [20480/50000 (45%)]\tLoss: 0.097394, Accuracy: 96.48\n",
      "Train Epoch: 54 [21760/50000 (48%)]\tLoss: 0.151617, Accuracy: 93.75\n",
      "Train Epoch: 54 [23040/50000 (51%)]\tLoss: 0.105259, Accuracy: 96.48\n",
      "Train Epoch: 54 [24320/50000 (54%)]\tLoss: 0.141511, Accuracy: 95.31\n",
      "Train Epoch: 54 [25600/50000 (57%)]\tLoss: 0.147227, Accuracy: 94.53\n",
      "Train Epoch: 54 [26880/50000 (60%)]\tLoss: 0.089642, Accuracy: 97.27\n",
      "Train Epoch: 54 [28160/50000 (62%)]\tLoss: 0.089050, Accuracy: 96.48\n",
      "Train Epoch: 54 [29440/50000 (65%)]\tLoss: 0.108954, Accuracy: 95.70\n",
      "Train Epoch: 54 [30720/50000 (68%)]\tLoss: 0.112864, Accuracy: 96.09\n",
      "Train Epoch: 54 [32000/50000 (71%)]\tLoss: 0.087198, Accuracy: 97.27\n",
      "Train Epoch: 54 [33280/50000 (74%)]\tLoss: 0.083811, Accuracy: 97.66\n",
      "Train Epoch: 54 [34560/50000 (77%)]\tLoss: 0.127521, Accuracy: 94.92\n",
      "Train Epoch: 54 [35840/50000 (80%)]\tLoss: 0.122499, Accuracy: 94.92\n",
      "Train Epoch: 54 [37120/50000 (82%)]\tLoss: 0.179103, Accuracy: 93.75\n",
      "Train Epoch: 54 [38400/50000 (85%)]\tLoss: 0.107404, Accuracy: 97.27\n",
      "Train Epoch: 54 [39680/50000 (88%)]\tLoss: 0.078999, Accuracy: 97.66\n",
      "Train Epoch: 54 [40960/50000 (91%)]\tLoss: 0.061378, Accuracy: 98.44\n",
      "Train Epoch: 54 [42240/50000 (94%)]\tLoss: 0.101729, Accuracy: 96.48\n",
      "Train Epoch: 54 [43520/50000 (97%)]\tLoss: 0.106348, Accuracy: 96.88\n",
      "Train Epoch: 54 [35000/50000 (99%)]\tLoss: 0.082880, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.4153, Accuracy: 4446/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.428613424301147 s]\n",
      "Train Epoch: 55 [0/50000 (0%)]\tLoss: 0.069365, Accuracy: 97.66\n",
      "Train Epoch: 55 [1280/50000 (3%)]\tLoss: 0.101409, Accuracy: 96.48\n",
      "Train Epoch: 55 [2560/50000 (6%)]\tLoss: 0.097651, Accuracy: 96.88\n",
      "Train Epoch: 55 [3840/50000 (9%)]\tLoss: 0.067336, Accuracy: 97.66\n",
      "Train Epoch: 55 [5120/50000 (11%)]\tLoss: 0.129193, Accuracy: 94.92\n",
      "Train Epoch: 55 [6400/50000 (14%)]\tLoss: 0.094872, Accuracy: 97.27\n",
      "Train Epoch: 55 [7680/50000 (17%)]\tLoss: 0.076850, Accuracy: 96.88\n",
      "Train Epoch: 55 [8960/50000 (20%)]\tLoss: 0.082856, Accuracy: 96.48\n",
      "Train Epoch: 55 [10240/50000 (23%)]\tLoss: 0.057333, Accuracy: 97.66\n",
      "Train Epoch: 55 [11520/50000 (26%)]\tLoss: 0.077972, Accuracy: 98.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 55 [12800/50000 (28%)]\tLoss: 0.059674, Accuracy: 98.83\n",
      "Train Epoch: 55 [14080/50000 (31%)]\tLoss: 0.154287, Accuracy: 94.92\n",
      "Train Epoch: 55 [15360/50000 (34%)]\tLoss: 0.117040, Accuracy: 96.09\n",
      "Train Epoch: 55 [16640/50000 (37%)]\tLoss: 0.066256, Accuracy: 98.83\n",
      "Train Epoch: 55 [17920/50000 (40%)]\tLoss: 0.124848, Accuracy: 95.70\n",
      "Train Epoch: 55 [19200/50000 (43%)]\tLoss: 0.101256, Accuracy: 96.48\n",
      "Train Epoch: 55 [20480/50000 (45%)]\tLoss: 0.097290, Accuracy: 96.09\n",
      "Train Epoch: 55 [21760/50000 (48%)]\tLoss: 0.084995, Accuracy: 96.48\n",
      "Train Epoch: 55 [23040/50000 (51%)]\tLoss: 0.055907, Accuracy: 97.66\n",
      "Train Epoch: 55 [24320/50000 (54%)]\tLoss: 0.102942, Accuracy: 96.48\n",
      "Train Epoch: 55 [25600/50000 (57%)]\tLoss: 0.193235, Accuracy: 93.36\n",
      "Train Epoch: 55 [26880/50000 (60%)]\tLoss: 0.115858, Accuracy: 96.88\n",
      "Train Epoch: 55 [28160/50000 (62%)]\tLoss: 0.094895, Accuracy: 97.66\n",
      "Train Epoch: 55 [29440/50000 (65%)]\tLoss: 0.170044, Accuracy: 94.14\n",
      "Train Epoch: 55 [30720/50000 (68%)]\tLoss: 0.276846, Accuracy: 91.80\n",
      "Train Epoch: 55 [32000/50000 (71%)]\tLoss: 0.102376, Accuracy: 95.31\n",
      "Train Epoch: 55 [33280/50000 (74%)]\tLoss: 0.122357, Accuracy: 95.70\n",
      "Train Epoch: 55 [34560/50000 (77%)]\tLoss: 0.097390, Accuracy: 96.48\n",
      "Train Epoch: 55 [35840/50000 (80%)]\tLoss: 0.107759, Accuracy: 96.88\n",
      "Train Epoch: 55 [37120/50000 (82%)]\tLoss: 0.062333, Accuracy: 97.27\n",
      "Train Epoch: 55 [38400/50000 (85%)]\tLoss: 0.100744, Accuracy: 94.92\n",
      "Train Epoch: 55 [39680/50000 (88%)]\tLoss: 0.151795, Accuracy: 96.09\n",
      "Train Epoch: 55 [40960/50000 (91%)]\tLoss: 0.105799, Accuracy: 96.48\n",
      "Train Epoch: 55 [42240/50000 (94%)]\tLoss: 0.080591, Accuracy: 98.05\n",
      "Train Epoch: 55 [43520/50000 (97%)]\tLoss: 0.134031, Accuracy: 94.53\n",
      "Train Epoch: 55 [35000/50000 (99%)]\tLoss: 0.121823, Accuracy: 96.00\n",
      "\n",
      "Validation set: Average loss: 0.4235, Accuracy: 4418/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.43956470489502 s]\n",
      "Train Epoch: 56 [0/50000 (0%)]\tLoss: 0.134456, Accuracy: 94.14\n",
      "Train Epoch: 56 [1280/50000 (3%)]\tLoss: 0.093541, Accuracy: 96.09\n",
      "Train Epoch: 56 [2560/50000 (6%)]\tLoss: 0.084921, Accuracy: 96.48\n",
      "Train Epoch: 56 [3840/50000 (9%)]\tLoss: 0.089175, Accuracy: 96.88\n",
      "Train Epoch: 56 [5120/50000 (11%)]\tLoss: 0.079646, Accuracy: 97.27\n",
      "Train Epoch: 56 [6400/50000 (14%)]\tLoss: 0.102904, Accuracy: 97.27\n",
      "Train Epoch: 56 [7680/50000 (17%)]\tLoss: 0.065698, Accuracy: 98.44\n",
      "Train Epoch: 56 [8960/50000 (20%)]\tLoss: 0.050936, Accuracy: 98.44\n",
      "Train Epoch: 56 [10240/50000 (23%)]\tLoss: 0.099740, Accuracy: 97.66\n",
      "Train Epoch: 56 [11520/50000 (26%)]\tLoss: 0.212140, Accuracy: 94.14\n",
      "Train Epoch: 56 [12800/50000 (28%)]\tLoss: 0.095597, Accuracy: 95.70\n",
      "Train Epoch: 56 [14080/50000 (31%)]\tLoss: 0.106848, Accuracy: 96.09\n",
      "Train Epoch: 56 [15360/50000 (34%)]\tLoss: 0.129742, Accuracy: 95.70\n",
      "Train Epoch: 56 [16640/50000 (37%)]\tLoss: 0.090954, Accuracy: 96.88\n",
      "Train Epoch: 56 [17920/50000 (40%)]\tLoss: 0.061589, Accuracy: 98.83\n",
      "Train Epoch: 56 [19200/50000 (43%)]\tLoss: 0.113049, Accuracy: 95.31\n",
      "Train Epoch: 56 [20480/50000 (45%)]\tLoss: 0.120627, Accuracy: 96.48\n",
      "Train Epoch: 56 [21760/50000 (48%)]\tLoss: 0.135965, Accuracy: 94.14\n",
      "Train Epoch: 56 [23040/50000 (51%)]\tLoss: 0.092386, Accuracy: 97.66\n",
      "Train Epoch: 56 [24320/50000 (54%)]\tLoss: 0.111761, Accuracy: 96.88\n",
      "Train Epoch: 56 [25600/50000 (57%)]\tLoss: 0.099287, Accuracy: 94.53\n",
      "Train Epoch: 56 [26880/50000 (60%)]\tLoss: 0.061674, Accuracy: 97.27\n",
      "Train Epoch: 56 [28160/50000 (62%)]\tLoss: 0.094130, Accuracy: 96.88\n",
      "Train Epoch: 56 [29440/50000 (65%)]\tLoss: 0.089123, Accuracy: 97.66\n",
      "Train Epoch: 56 [30720/50000 (68%)]\tLoss: 0.098759, Accuracy: 95.70\n",
      "Train Epoch: 56 [32000/50000 (71%)]\tLoss: 0.090605, Accuracy: 96.88\n",
      "Train Epoch: 56 [33280/50000 (74%)]\tLoss: 0.078107, Accuracy: 96.48\n",
      "Train Epoch: 56 [34560/50000 (77%)]\tLoss: 0.152893, Accuracy: 96.48\n",
      "Train Epoch: 56 [35840/50000 (80%)]\tLoss: 0.083193, Accuracy: 97.66\n",
      "Train Epoch: 56 [37120/50000 (82%)]\tLoss: 0.108407, Accuracy: 97.66\n",
      "Train Epoch: 56 [38400/50000 (85%)]\tLoss: 0.129766, Accuracy: 94.14\n",
      "Train Epoch: 56 [39680/50000 (88%)]\tLoss: 0.122754, Accuracy: 95.31\n",
      "Train Epoch: 56 [40960/50000 (91%)]\tLoss: 0.147422, Accuracy: 94.92\n",
      "Train Epoch: 56 [42240/50000 (94%)]\tLoss: 0.107012, Accuracy: 96.88\n",
      "Train Epoch: 56 [43520/50000 (97%)]\tLoss: 0.132100, Accuracy: 96.09\n",
      "Train Epoch: 56 [35000/50000 (99%)]\tLoss: 0.102751, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.4249, Accuracy: 4433/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.412702083587646 s]\n",
      "Train Epoch: 57 [0/50000 (0%)]\tLoss: 0.094362, Accuracy: 94.92\n",
      "Train Epoch: 57 [1280/50000 (3%)]\tLoss: 0.106080, Accuracy: 96.88\n",
      "Train Epoch: 57 [2560/50000 (6%)]\tLoss: 0.089462, Accuracy: 97.27\n",
      "Train Epoch: 57 [3840/50000 (9%)]\tLoss: 0.108179, Accuracy: 97.27\n",
      "Train Epoch: 57 [5120/50000 (11%)]\tLoss: 0.087985, Accuracy: 95.70\n",
      "Train Epoch: 57 [6400/50000 (14%)]\tLoss: 0.164361, Accuracy: 92.97\n",
      "Train Epoch: 57 [7680/50000 (17%)]\tLoss: 0.050202, Accuracy: 98.83\n",
      "Train Epoch: 57 [8960/50000 (20%)]\tLoss: 0.129402, Accuracy: 94.92\n",
      "Train Epoch: 57 [10240/50000 (23%)]\tLoss: 0.085718, Accuracy: 97.66\n",
      "Train Epoch: 57 [11520/50000 (26%)]\tLoss: 0.095115, Accuracy: 97.66\n",
      "Train Epoch: 57 [12800/50000 (28%)]\tLoss: 0.075514, Accuracy: 97.27\n",
      "Train Epoch: 57 [14080/50000 (31%)]\tLoss: 0.065312, Accuracy: 98.44\n",
      "Train Epoch: 57 [15360/50000 (34%)]\tLoss: 0.122371, Accuracy: 96.09\n",
      "Train Epoch: 57 [16640/50000 (37%)]\tLoss: 0.068507, Accuracy: 97.27\n",
      "Train Epoch: 57 [17920/50000 (40%)]\tLoss: 0.140172, Accuracy: 94.92\n",
      "Train Epoch: 57 [19200/50000 (43%)]\tLoss: 0.053513, Accuracy: 98.05\n",
      "Train Epoch: 57 [20480/50000 (45%)]\tLoss: 0.065575, Accuracy: 97.27\n",
      "Train Epoch: 57 [21760/50000 (48%)]\tLoss: 0.120226, Accuracy: 96.88\n",
      "Train Epoch: 57 [23040/50000 (51%)]\tLoss: 0.077822, Accuracy: 96.48\n",
      "Train Epoch: 57 [24320/50000 (54%)]\tLoss: 0.070777, Accuracy: 98.44\n",
      "Train Epoch: 57 [25600/50000 (57%)]\tLoss: 0.139333, Accuracy: 95.31\n",
      "Train Epoch: 57 [26880/50000 (60%)]\tLoss: 0.096930, Accuracy: 96.48\n",
      "Train Epoch: 57 [28160/50000 (62%)]\tLoss: 0.123889, Accuracy: 96.48\n",
      "Train Epoch: 57 [29440/50000 (65%)]\tLoss: 0.098232, Accuracy: 97.27\n",
      "Train Epoch: 57 [30720/50000 (68%)]\tLoss: 0.116395, Accuracy: 96.09\n",
      "Train Epoch: 57 [32000/50000 (71%)]\tLoss: 0.142909, Accuracy: 95.31\n",
      "Train Epoch: 57 [33280/50000 (74%)]\tLoss: 0.066575, Accuracy: 97.27\n",
      "Train Epoch: 57 [34560/50000 (77%)]\tLoss: 0.066429, Accuracy: 97.66\n",
      "Train Epoch: 57 [35840/50000 (80%)]\tLoss: 0.125503, Accuracy: 95.70\n",
      "Train Epoch: 57 [37120/50000 (82%)]\tLoss: 0.075625, Accuracy: 98.44\n",
      "Train Epoch: 57 [38400/50000 (85%)]\tLoss: 0.079229, Accuracy: 96.88\n",
      "Train Epoch: 57 [39680/50000 (88%)]\tLoss: 0.105955, Accuracy: 94.92\n",
      "Train Epoch: 57 [40960/50000 (91%)]\tLoss: 0.137167, Accuracy: 94.92\n",
      "Train Epoch: 57 [42240/50000 (94%)]\tLoss: 0.076475, Accuracy: 97.27\n",
      "Train Epoch: 57 [43520/50000 (97%)]\tLoss: 0.106940, Accuracy: 95.70\n",
      "Train Epoch: 57 [35000/50000 (99%)]\tLoss: 0.064544, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.4208, Accuracy: 4423/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.37576961517334 s]\n",
      "Train Epoch: 58 [0/50000 (0%)]\tLoss: 0.088766, Accuracy: 96.88\n",
      "Train Epoch: 58 [1280/50000 (3%)]\tLoss: 0.155219, Accuracy: 95.31\n",
      "Train Epoch: 58 [2560/50000 (6%)]\tLoss: 0.105709, Accuracy: 95.31\n",
      "Train Epoch: 58 [3840/50000 (9%)]\tLoss: 0.094386, Accuracy: 96.09\n",
      "Train Epoch: 58 [5120/50000 (11%)]\tLoss: 0.129253, Accuracy: 94.53\n",
      "Train Epoch: 58 [6400/50000 (14%)]\tLoss: 0.053304, Accuracy: 98.44\n",
      "Train Epoch: 58 [7680/50000 (17%)]\tLoss: 0.070213, Accuracy: 96.88\n",
      "Train Epoch: 58 [8960/50000 (20%)]\tLoss: 0.093291, Accuracy: 96.48\n",
      "Train Epoch: 58 [10240/50000 (23%)]\tLoss: 0.138812, Accuracy: 94.53\n",
      "Train Epoch: 58 [11520/50000 (26%)]\tLoss: 0.088416, Accuracy: 96.48\n",
      "Train Epoch: 58 [12800/50000 (28%)]\tLoss: 0.127403, Accuracy: 94.92\n",
      "Train Epoch: 58 [14080/50000 (31%)]\tLoss: 0.110340, Accuracy: 96.88\n",
      "Train Epoch: 58 [15360/50000 (34%)]\tLoss: 0.155226, Accuracy: 95.31\n",
      "Train Epoch: 58 [16640/50000 (37%)]\tLoss: 0.077545, Accuracy: 97.27\n",
      "Train Epoch: 58 [17920/50000 (40%)]\tLoss: 0.147605, Accuracy: 94.92\n",
      "Train Epoch: 58 [19200/50000 (43%)]\tLoss: 0.085614, Accuracy: 96.48\n",
      "Train Epoch: 58 [20480/50000 (45%)]\tLoss: 0.159103, Accuracy: 93.36\n",
      "Train Epoch: 58 [21760/50000 (48%)]\tLoss: 0.096674, Accuracy: 96.88\n",
      "Train Epoch: 58 [23040/50000 (51%)]\tLoss: 0.092673, Accuracy: 95.70\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 58 [24320/50000 (54%)]\tLoss: 0.052689, Accuracy: 98.44\n",
      "Train Epoch: 58 [25600/50000 (57%)]\tLoss: 0.096973, Accuracy: 96.48\n",
      "Train Epoch: 58 [26880/50000 (60%)]\tLoss: 0.123833, Accuracy: 96.48\n",
      "Train Epoch: 58 [28160/50000 (62%)]\tLoss: 0.061920, Accuracy: 98.05\n",
      "Train Epoch: 58 [29440/50000 (65%)]\tLoss: 0.099897, Accuracy: 97.27\n",
      "Train Epoch: 58 [30720/50000 (68%)]\tLoss: 0.040162, Accuracy: 98.44\n",
      "Train Epoch: 58 [32000/50000 (71%)]\tLoss: 0.081028, Accuracy: 96.88\n",
      "Train Epoch: 58 [33280/50000 (74%)]\tLoss: 0.118592, Accuracy: 95.70\n",
      "Train Epoch: 58 [34560/50000 (77%)]\tLoss: 0.050512, Accuracy: 98.83\n",
      "Train Epoch: 58 [35840/50000 (80%)]\tLoss: 0.091718, Accuracy: 96.09\n",
      "Train Epoch: 58 [37120/50000 (82%)]\tLoss: 0.117267, Accuracy: 96.09\n",
      "Train Epoch: 58 [38400/50000 (85%)]\tLoss: 0.104097, Accuracy: 95.70\n",
      "Train Epoch: 58 [39680/50000 (88%)]\tLoss: 0.157671, Accuracy: 94.92\n",
      "Train Epoch: 58 [40960/50000 (91%)]\tLoss: 0.138754, Accuracy: 95.31\n",
      "Train Epoch: 58 [42240/50000 (94%)]\tLoss: 0.090068, Accuracy: 97.66\n",
      "Train Epoch: 58 [43520/50000 (97%)]\tLoss: 0.111656, Accuracy: 95.70\n",
      "Train Epoch: 58 [35000/50000 (99%)]\tLoss: 0.178899, Accuracy: 93.00\n",
      "\n",
      "Validation set: Average loss: 0.4208, Accuracy: 4434/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.344943284988403 s]\n",
      "Train Epoch: 59 [0/50000 (0%)]\tLoss: 0.068243, Accuracy: 97.27\n",
      "Train Epoch: 59 [1280/50000 (3%)]\tLoss: 0.073419, Accuracy: 97.66\n",
      "Train Epoch: 59 [2560/50000 (6%)]\tLoss: 0.071255, Accuracy: 98.05\n",
      "Train Epoch: 59 [3840/50000 (9%)]\tLoss: 0.149848, Accuracy: 94.92\n",
      "Train Epoch: 59 [5120/50000 (11%)]\tLoss: 0.055941, Accuracy: 97.66\n",
      "Train Epoch: 59 [6400/50000 (14%)]\tLoss: 0.089927, Accuracy: 97.66\n",
      "Train Epoch: 59 [7680/50000 (17%)]\tLoss: 0.068579, Accuracy: 98.44\n",
      "Train Epoch: 59 [8960/50000 (20%)]\tLoss: 0.104730, Accuracy: 96.88\n",
      "Train Epoch: 59 [10240/50000 (23%)]\tLoss: 0.068522, Accuracy: 97.66\n",
      "Train Epoch: 59 [11520/50000 (26%)]\tLoss: 0.070100, Accuracy: 97.66\n",
      "Train Epoch: 59 [12800/50000 (28%)]\tLoss: 0.099006, Accuracy: 96.09\n",
      "Train Epoch: 59 [14080/50000 (31%)]\tLoss: 0.097433, Accuracy: 96.88\n",
      "Train Epoch: 59 [15360/50000 (34%)]\tLoss: 0.118372, Accuracy: 95.70\n",
      "Train Epoch: 59 [16640/50000 (37%)]\tLoss: 0.184385, Accuracy: 93.36\n",
      "Train Epoch: 59 [17920/50000 (40%)]\tLoss: 0.092597, Accuracy: 98.44\n",
      "Train Epoch: 59 [19200/50000 (43%)]\tLoss: 0.101767, Accuracy: 96.09\n",
      "Train Epoch: 59 [20480/50000 (45%)]\tLoss: 0.140949, Accuracy: 94.14\n",
      "Train Epoch: 59 [21760/50000 (48%)]\tLoss: 0.144379, Accuracy: 95.70\n",
      "Train Epoch: 59 [23040/50000 (51%)]\tLoss: 0.098121, Accuracy: 94.92\n",
      "Train Epoch: 59 [24320/50000 (54%)]\tLoss: 0.067109, Accuracy: 97.66\n",
      "Train Epoch: 59 [25600/50000 (57%)]\tLoss: 0.149954, Accuracy: 95.70\n",
      "Train Epoch: 59 [26880/50000 (60%)]\tLoss: 0.123351, Accuracy: 95.70\n",
      "Train Epoch: 59 [28160/50000 (62%)]\tLoss: 0.108199, Accuracy: 96.09\n",
      "Train Epoch: 59 [29440/50000 (65%)]\tLoss: 0.085560, Accuracy: 98.05\n",
      "Train Epoch: 59 [30720/50000 (68%)]\tLoss: 0.088226, Accuracy: 96.48\n",
      "Train Epoch: 59 [32000/50000 (71%)]\tLoss: 0.160468, Accuracy: 95.31\n",
      "Train Epoch: 59 [33280/50000 (74%)]\tLoss: 0.111688, Accuracy: 96.48\n",
      "Train Epoch: 59 [34560/50000 (77%)]\tLoss: 0.146086, Accuracy: 95.70\n",
      "Train Epoch: 59 [35840/50000 (80%)]\tLoss: 0.103823, Accuracy: 96.48\n",
      "Train Epoch: 59 [37120/50000 (82%)]\tLoss: 0.094130, Accuracy: 96.88\n",
      "Train Epoch: 59 [38400/50000 (85%)]\tLoss: 0.109878, Accuracy: 95.70\n",
      "Train Epoch: 59 [39680/50000 (88%)]\tLoss: 0.136815, Accuracy: 95.70\n",
      "Train Epoch: 59 [40960/50000 (91%)]\tLoss: 0.152695, Accuracy: 93.75\n",
      "Train Epoch: 59 [42240/50000 (94%)]\tLoss: 0.143575, Accuracy: 94.53\n",
      "Train Epoch: 59 [43520/50000 (97%)]\tLoss: 0.104583, Accuracy: 96.09\n",
      "Train Epoch: 59 [35000/50000 (99%)]\tLoss: 0.100992, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.3960, Accuracy: 4459/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.359034299850464 s]\n",
      "Train Epoch: 60 [0/50000 (0%)]\tLoss: 0.103544, Accuracy: 96.09\n",
      "Train Epoch: 60 [1280/50000 (3%)]\tLoss: 0.041763, Accuracy: 99.22\n",
      "Train Epoch: 60 [2560/50000 (6%)]\tLoss: 0.084106, Accuracy: 96.48\n",
      "Train Epoch: 60 [3840/50000 (9%)]\tLoss: 0.055582, Accuracy: 97.66\n",
      "Train Epoch: 60 [5120/50000 (11%)]\tLoss: 0.107761, Accuracy: 95.70\n",
      "Train Epoch: 60 [6400/50000 (14%)]\tLoss: 0.106789, Accuracy: 96.88\n",
      "Train Epoch: 60 [7680/50000 (17%)]\tLoss: 0.090643, Accuracy: 96.88\n",
      "Train Epoch: 60 [8960/50000 (20%)]\tLoss: 0.080084, Accuracy: 96.88\n",
      "Train Epoch: 60 [10240/50000 (23%)]\tLoss: 0.070169, Accuracy: 98.05\n",
      "Train Epoch: 60 [11520/50000 (26%)]\tLoss: 0.049138, Accuracy: 97.66\n",
      "Train Epoch: 60 [12800/50000 (28%)]\tLoss: 0.134870, Accuracy: 95.31\n",
      "Train Epoch: 60 [14080/50000 (31%)]\tLoss: 0.105939, Accuracy: 95.70\n",
      "Train Epoch: 60 [15360/50000 (34%)]\tLoss: 0.102767, Accuracy: 96.88\n",
      "Train Epoch: 60 [16640/50000 (37%)]\tLoss: 0.108593, Accuracy: 96.48\n",
      "Train Epoch: 60 [17920/50000 (40%)]\tLoss: 0.062065, Accuracy: 98.44\n",
      "Train Epoch: 60 [19200/50000 (43%)]\tLoss: 0.093257, Accuracy: 97.27\n",
      "Train Epoch: 60 [20480/50000 (45%)]\tLoss: 0.089008, Accuracy: 96.09\n",
      "Train Epoch: 60 [21760/50000 (48%)]\tLoss: 0.076680, Accuracy: 97.27\n",
      "Train Epoch: 60 [23040/50000 (51%)]\tLoss: 0.046805, Accuracy: 98.83\n",
      "Train Epoch: 60 [24320/50000 (54%)]\tLoss: 0.079961, Accuracy: 96.88\n",
      "Train Epoch: 60 [25600/50000 (57%)]\tLoss: 0.066339, Accuracy: 97.66\n",
      "Train Epoch: 60 [26880/50000 (60%)]\tLoss: 0.101109, Accuracy: 96.48\n",
      "Train Epoch: 60 [28160/50000 (62%)]\tLoss: 0.121467, Accuracy: 95.70\n",
      "Train Epoch: 60 [29440/50000 (65%)]\tLoss: 0.091394, Accuracy: 95.70\n",
      "Train Epoch: 60 [30720/50000 (68%)]\tLoss: 0.064860, Accuracy: 97.27\n",
      "Train Epoch: 60 [32000/50000 (71%)]\tLoss: 0.178081, Accuracy: 95.70\n",
      "Train Epoch: 60 [33280/50000 (74%)]\tLoss: 0.073391, Accuracy: 97.27\n",
      "Train Epoch: 60 [34560/50000 (77%)]\tLoss: 0.082472, Accuracy: 95.70\n",
      "Train Epoch: 60 [35840/50000 (80%)]\tLoss: 0.119310, Accuracy: 95.70\n",
      "Train Epoch: 60 [37120/50000 (82%)]\tLoss: 0.094345, Accuracy: 96.48\n",
      "Train Epoch: 60 [38400/50000 (85%)]\tLoss: 0.146110, Accuracy: 95.31\n",
      "Train Epoch: 60 [39680/50000 (88%)]\tLoss: 0.076164, Accuracy: 97.66\n",
      "Train Epoch: 60 [40960/50000 (91%)]\tLoss: 0.093812, Accuracy: 96.09\n",
      "Train Epoch: 60 [42240/50000 (94%)]\tLoss: 0.090494, Accuracy: 97.27\n",
      "Train Epoch: 60 [43520/50000 (97%)]\tLoss: 0.121159, Accuracy: 96.48\n",
      "Train Epoch: 60 [35000/50000 (99%)]\tLoss: 0.083129, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.4311, Accuracy: 4431/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.38509726524353 s]\n",
      "Train Epoch: 61 [0/50000 (0%)]\tLoss: 0.083975, Accuracy: 96.48\n",
      "Train Epoch: 61 [1280/50000 (3%)]\tLoss: 0.111973, Accuracy: 95.70\n",
      "Train Epoch: 61 [2560/50000 (6%)]\tLoss: 0.108842, Accuracy: 95.31\n",
      "Train Epoch: 61 [3840/50000 (9%)]\tLoss: 0.039067, Accuracy: 98.83\n",
      "Train Epoch: 61 [5120/50000 (11%)]\tLoss: 0.095086, Accuracy: 95.70\n",
      "Train Epoch: 61 [6400/50000 (14%)]\tLoss: 0.069207, Accuracy: 97.66\n",
      "Train Epoch: 61 [7680/50000 (17%)]\tLoss: 0.102563, Accuracy: 97.66\n",
      "Train Epoch: 61 [8960/50000 (20%)]\tLoss: 0.073398, Accuracy: 97.66\n",
      "Train Epoch: 61 [10240/50000 (23%)]\tLoss: 0.068287, Accuracy: 97.27\n",
      "Train Epoch: 61 [11520/50000 (26%)]\tLoss: 0.119026, Accuracy: 96.09\n",
      "Train Epoch: 61 [12800/50000 (28%)]\tLoss: 0.052301, Accuracy: 98.05\n",
      "Train Epoch: 61 [14080/50000 (31%)]\tLoss: 0.067915, Accuracy: 96.88\n",
      "Train Epoch: 61 [15360/50000 (34%)]\tLoss: 0.076654, Accuracy: 97.27\n",
      "Train Epoch: 61 [16640/50000 (37%)]\tLoss: 0.060786, Accuracy: 96.88\n",
      "Train Epoch: 61 [17920/50000 (40%)]\tLoss: 0.121105, Accuracy: 95.31\n",
      "Train Epoch: 61 [19200/50000 (43%)]\tLoss: 0.074898, Accuracy: 95.70\n",
      "Train Epoch: 61 [20480/50000 (45%)]\tLoss: 0.096843, Accuracy: 96.09\n",
      "Train Epoch: 61 [21760/50000 (48%)]\tLoss: 0.073682, Accuracy: 98.05\n",
      "Train Epoch: 61 [23040/50000 (51%)]\tLoss: 0.067979, Accuracy: 97.66\n",
      "Train Epoch: 61 [24320/50000 (54%)]\tLoss: 0.086602, Accuracy: 97.66\n",
      "Train Epoch: 61 [25600/50000 (57%)]\tLoss: 0.055774, Accuracy: 97.66\n",
      "Train Epoch: 61 [26880/50000 (60%)]\tLoss: 0.071334, Accuracy: 96.88\n",
      "Train Epoch: 61 [28160/50000 (62%)]\tLoss: 0.090589, Accuracy: 97.27\n",
      "Train Epoch: 61 [29440/50000 (65%)]\tLoss: 0.082177, Accuracy: 98.05\n",
      "Train Epoch: 61 [30720/50000 (68%)]\tLoss: 0.113990, Accuracy: 95.31\n",
      "Train Epoch: 61 [32000/50000 (71%)]\tLoss: 0.086203, Accuracy: 96.88\n",
      "Train Epoch: 61 [33280/50000 (74%)]\tLoss: 0.072240, Accuracy: 97.27\n",
      "Train Epoch: 61 [34560/50000 (77%)]\tLoss: 0.104858, Accuracy: 96.09\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 61 [35840/50000 (80%)]\tLoss: 0.062030, Accuracy: 97.66\n",
      "Train Epoch: 61 [37120/50000 (82%)]\tLoss: 0.047579, Accuracy: 98.05\n",
      "Train Epoch: 61 [38400/50000 (85%)]\tLoss: 0.102669, Accuracy: 96.48\n",
      "Train Epoch: 61 [39680/50000 (88%)]\tLoss: 0.084550, Accuracy: 96.88\n",
      "Train Epoch: 61 [40960/50000 (91%)]\tLoss: 0.083697, Accuracy: 98.05\n",
      "Train Epoch: 61 [42240/50000 (94%)]\tLoss: 0.099748, Accuracy: 97.66\n",
      "Train Epoch: 61 [43520/50000 (97%)]\tLoss: 0.096808, Accuracy: 96.88\n",
      "Train Epoch: 61 [35000/50000 (99%)]\tLoss: 0.058908, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.4082, Accuracy: 4458/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.380900859832764 s]\n",
      "Train Epoch: 62 [0/50000 (0%)]\tLoss: 0.096817, Accuracy: 96.48\n",
      "Train Epoch: 62 [1280/50000 (3%)]\tLoss: 0.104727, Accuracy: 96.48\n",
      "Train Epoch: 62 [2560/50000 (6%)]\tLoss: 0.071415, Accuracy: 97.66\n",
      "Train Epoch: 62 [3840/50000 (9%)]\tLoss: 0.065315, Accuracy: 98.05\n",
      "Train Epoch: 62 [5120/50000 (11%)]\tLoss: 0.065890, Accuracy: 97.66\n",
      "Train Epoch: 62 [6400/50000 (14%)]\tLoss: 0.068333, Accuracy: 97.66\n",
      "Train Epoch: 62 [7680/50000 (17%)]\tLoss: 0.044210, Accuracy: 98.83\n",
      "Train Epoch: 62 [8960/50000 (20%)]\tLoss: 0.055022, Accuracy: 98.44\n",
      "Train Epoch: 62 [10240/50000 (23%)]\tLoss: 0.145171, Accuracy: 94.53\n",
      "Train Epoch: 62 [11520/50000 (26%)]\tLoss: 0.080924, Accuracy: 98.05\n",
      "Train Epoch: 62 [12800/50000 (28%)]\tLoss: 0.100694, Accuracy: 96.48\n",
      "Train Epoch: 62 [14080/50000 (31%)]\tLoss: 0.041392, Accuracy: 99.22\n",
      "Train Epoch: 62 [15360/50000 (34%)]\tLoss: 0.089003, Accuracy: 96.48\n",
      "Train Epoch: 62 [16640/50000 (37%)]\tLoss: 0.040644, Accuracy: 98.44\n",
      "Train Epoch: 62 [17920/50000 (40%)]\tLoss: 0.119313, Accuracy: 94.92\n",
      "Train Epoch: 62 [19200/50000 (43%)]\tLoss: 0.054721, Accuracy: 97.27\n",
      "Train Epoch: 62 [20480/50000 (45%)]\tLoss: 0.069017, Accuracy: 97.66\n",
      "Train Epoch: 62 [21760/50000 (48%)]\tLoss: 0.062878, Accuracy: 97.66\n",
      "Train Epoch: 62 [23040/50000 (51%)]\tLoss: 0.058514, Accuracy: 97.27\n",
      "Train Epoch: 62 [24320/50000 (54%)]\tLoss: 0.046499, Accuracy: 97.66\n",
      "Train Epoch: 62 [25600/50000 (57%)]\tLoss: 0.112192, Accuracy: 96.48\n",
      "Train Epoch: 62 [26880/50000 (60%)]\tLoss: 0.062807, Accuracy: 98.05\n",
      "Train Epoch: 62 [28160/50000 (62%)]\tLoss: 0.045158, Accuracy: 98.44\n",
      "Train Epoch: 62 [29440/50000 (65%)]\tLoss: 0.055296, Accuracy: 98.83\n",
      "Train Epoch: 62 [30720/50000 (68%)]\tLoss: 0.084457, Accuracy: 96.09\n",
      "Train Epoch: 62 [32000/50000 (71%)]\tLoss: 0.055949, Accuracy: 97.66\n",
      "Train Epoch: 62 [33280/50000 (74%)]\tLoss: 0.080528, Accuracy: 98.05\n",
      "Train Epoch: 62 [34560/50000 (77%)]\tLoss: 0.090406, Accuracy: 96.48\n",
      "Train Epoch: 62 [35840/50000 (80%)]\tLoss: 0.086156, Accuracy: 96.88\n",
      "Train Epoch: 62 [37120/50000 (82%)]\tLoss: 0.079633, Accuracy: 97.27\n",
      "Train Epoch: 62 [38400/50000 (85%)]\tLoss: 0.081977, Accuracy: 96.88\n",
      "Train Epoch: 62 [39680/50000 (88%)]\tLoss: 0.047085, Accuracy: 98.44\n",
      "Train Epoch: 62 [40960/50000 (91%)]\tLoss: 0.099890, Accuracy: 95.31\n",
      "Train Epoch: 62 [42240/50000 (94%)]\tLoss: 0.061837, Accuracy: 98.05\n",
      "Train Epoch: 62 [43520/50000 (97%)]\tLoss: 0.074562, Accuracy: 97.27\n",
      "Train Epoch: 62 [35000/50000 (99%)]\tLoss: 0.041354, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.4239, Accuracy: 4462/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.385393857955933 s]\n",
      "Train Epoch: 63 [0/50000 (0%)]\tLoss: 0.090206, Accuracy: 96.48\n",
      "Train Epoch: 63 [1280/50000 (3%)]\tLoss: 0.039821, Accuracy: 98.83\n",
      "Train Epoch: 63 [2560/50000 (6%)]\tLoss: 0.068248, Accuracy: 97.27\n",
      "Train Epoch: 63 [3840/50000 (9%)]\tLoss: 0.046293, Accuracy: 98.44\n",
      "Train Epoch: 63 [5120/50000 (11%)]\tLoss: 0.067379, Accuracy: 98.05\n",
      "Train Epoch: 63 [6400/50000 (14%)]\tLoss: 0.108474, Accuracy: 95.70\n",
      "Train Epoch: 63 [7680/50000 (17%)]\tLoss: 0.063153, Accuracy: 96.88\n",
      "Train Epoch: 63 [8960/50000 (20%)]\tLoss: 0.087075, Accuracy: 97.27\n",
      "Train Epoch: 63 [10240/50000 (23%)]\tLoss: 0.035449, Accuracy: 99.22\n",
      "Train Epoch: 63 [11520/50000 (26%)]\tLoss: 0.064710, Accuracy: 97.66\n",
      "Train Epoch: 63 [12800/50000 (28%)]\tLoss: 0.080109, Accuracy: 98.05\n",
      "Train Epoch: 63 [14080/50000 (31%)]\tLoss: 0.073600, Accuracy: 96.88\n",
      "Train Epoch: 63 [15360/50000 (34%)]\tLoss: 0.056740, Accuracy: 98.44\n",
      "Train Epoch: 63 [16640/50000 (37%)]\tLoss: 0.048974, Accuracy: 99.22\n",
      "Train Epoch: 63 [17920/50000 (40%)]\tLoss: 0.098331, Accuracy: 95.70\n",
      "Train Epoch: 63 [19200/50000 (43%)]\tLoss: 0.041492, Accuracy: 98.44\n",
      "Train Epoch: 63 [20480/50000 (45%)]\tLoss: 0.056606, Accuracy: 97.66\n",
      "Train Epoch: 63 [21760/50000 (48%)]\tLoss: 0.031395, Accuracy: 98.83\n",
      "Train Epoch: 63 [23040/50000 (51%)]\tLoss: 0.046837, Accuracy: 98.44\n",
      "Train Epoch: 63 [24320/50000 (54%)]\tLoss: 0.045132, Accuracy: 98.44\n",
      "Train Epoch: 63 [25600/50000 (57%)]\tLoss: 0.067964, Accuracy: 97.66\n",
      "Train Epoch: 63 [26880/50000 (60%)]\tLoss: 0.048679, Accuracy: 98.83\n",
      "Train Epoch: 63 [28160/50000 (62%)]\tLoss: 0.056243, Accuracy: 98.44\n",
      "Train Epoch: 63 [29440/50000 (65%)]\tLoss: 0.120071, Accuracy: 95.31\n",
      "Train Epoch: 63 [30720/50000 (68%)]\tLoss: 0.055736, Accuracy: 98.05\n",
      "Train Epoch: 63 [32000/50000 (71%)]\tLoss: 0.045444, Accuracy: 98.83\n",
      "Train Epoch: 63 [33280/50000 (74%)]\tLoss: 0.080389, Accuracy: 97.27\n",
      "Train Epoch: 63 [34560/50000 (77%)]\tLoss: 0.074344, Accuracy: 98.05\n",
      "Train Epoch: 63 [35840/50000 (80%)]\tLoss: 0.036717, Accuracy: 98.44\n",
      "Train Epoch: 63 [37120/50000 (82%)]\tLoss: 0.051303, Accuracy: 97.27\n",
      "Train Epoch: 63 [38400/50000 (85%)]\tLoss: 0.048968, Accuracy: 98.05\n",
      "Train Epoch: 63 [39680/50000 (88%)]\tLoss: 0.077595, Accuracy: 96.88\n",
      "Train Epoch: 63 [40960/50000 (91%)]\tLoss: 0.045928, Accuracy: 98.83\n",
      "Train Epoch: 63 [42240/50000 (94%)]\tLoss: 0.059043, Accuracy: 98.05\n",
      "Train Epoch: 63 [43520/50000 (97%)]\tLoss: 0.090963, Accuracy: 96.48\n",
      "Train Epoch: 63 [35000/50000 (99%)]\tLoss: 0.063327, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.4205, Accuracy: 4463/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.3726544380188 s]\n",
      "Train Epoch: 64 [0/50000 (0%)]\tLoss: 0.052155, Accuracy: 97.66\n",
      "Train Epoch: 64 [1280/50000 (3%)]\tLoss: 0.037737, Accuracy: 98.44\n",
      "Train Epoch: 64 [2560/50000 (6%)]\tLoss: 0.069738, Accuracy: 97.66\n",
      "Train Epoch: 64 [3840/50000 (9%)]\tLoss: 0.077063, Accuracy: 96.09\n",
      "Train Epoch: 64 [5120/50000 (11%)]\tLoss: 0.060117, Accuracy: 98.05\n",
      "Train Epoch: 64 [6400/50000 (14%)]\tLoss: 0.095791, Accuracy: 95.70\n",
      "Train Epoch: 64 [7680/50000 (17%)]\tLoss: 0.026244, Accuracy: 99.22\n",
      "Train Epoch: 64 [8960/50000 (20%)]\tLoss: 0.079088, Accuracy: 98.05\n",
      "Train Epoch: 64 [10240/50000 (23%)]\tLoss: 0.047094, Accuracy: 98.44\n",
      "Train Epoch: 64 [11520/50000 (26%)]\tLoss: 0.092442, Accuracy: 96.48\n",
      "Train Epoch: 64 [12800/50000 (28%)]\tLoss: 0.048798, Accuracy: 98.05\n",
      "Train Epoch: 64 [14080/50000 (31%)]\tLoss: 0.072290, Accuracy: 96.88\n",
      "Train Epoch: 64 [15360/50000 (34%)]\tLoss: 0.058874, Accuracy: 97.66\n",
      "Train Epoch: 64 [16640/50000 (37%)]\tLoss: 0.067963, Accuracy: 98.05\n",
      "Train Epoch: 64 [17920/50000 (40%)]\tLoss: 0.118287, Accuracy: 96.88\n",
      "Train Epoch: 64 [19200/50000 (43%)]\tLoss: 0.127468, Accuracy: 94.92\n",
      "Train Epoch: 64 [20480/50000 (45%)]\tLoss: 0.043197, Accuracy: 98.44\n",
      "Train Epoch: 64 [21760/50000 (48%)]\tLoss: 0.062017, Accuracy: 98.05\n",
      "Train Epoch: 64 [23040/50000 (51%)]\tLoss: 0.057662, Accuracy: 98.05\n",
      "Train Epoch: 64 [24320/50000 (54%)]\tLoss: 0.037354, Accuracy: 98.44\n",
      "Train Epoch: 64 [25600/50000 (57%)]\tLoss: 0.065347, Accuracy: 97.66\n",
      "Train Epoch: 64 [26880/50000 (60%)]\tLoss: 0.111412, Accuracy: 96.09\n",
      "Train Epoch: 64 [28160/50000 (62%)]\tLoss: 0.065162, Accuracy: 97.66\n",
      "Train Epoch: 64 [29440/50000 (65%)]\tLoss: 0.037969, Accuracy: 98.44\n",
      "Train Epoch: 64 [30720/50000 (68%)]\tLoss: 0.077410, Accuracy: 96.88\n",
      "Train Epoch: 64 [32000/50000 (71%)]\tLoss: 0.058400, Accuracy: 97.66\n",
      "Train Epoch: 64 [33280/50000 (74%)]\tLoss: 0.043728, Accuracy: 98.05\n",
      "Train Epoch: 64 [34560/50000 (77%)]\tLoss: 0.086890, Accuracy: 98.05\n",
      "Train Epoch: 64 [35840/50000 (80%)]\tLoss: 0.095272, Accuracy: 96.48\n",
      "Train Epoch: 64 [37120/50000 (82%)]\tLoss: 0.078250, Accuracy: 97.27\n",
      "Train Epoch: 64 [38400/50000 (85%)]\tLoss: 0.050306, Accuracy: 98.05\n",
      "Train Epoch: 64 [39680/50000 (88%)]\tLoss: 0.067202, Accuracy: 97.27\n",
      "Train Epoch: 64 [40960/50000 (91%)]\tLoss: 0.051279, Accuracy: 98.05\n",
      "Train Epoch: 64 [42240/50000 (94%)]\tLoss: 0.057166, Accuracy: 98.05\n",
      "Train Epoch: 64 [43520/50000 (97%)]\tLoss: 0.090314, Accuracy: 98.05\n",
      "Train Epoch: 64 [35000/50000 (99%)]\tLoss: 0.072351, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.4323, Accuracy: 4448/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.324822187423706 s]\n",
      "Train Epoch: 65 [0/50000 (0%)]\tLoss: 0.111371, Accuracy: 96.48\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 65 [1280/50000 (3%)]\tLoss: 0.049484, Accuracy: 98.44\n",
      "Train Epoch: 65 [2560/50000 (6%)]\tLoss: 0.060850, Accuracy: 97.66\n",
      "Train Epoch: 65 [3840/50000 (9%)]\tLoss: 0.059853, Accuracy: 98.05\n",
      "Train Epoch: 65 [5120/50000 (11%)]\tLoss: 0.088819, Accuracy: 95.70\n",
      "Train Epoch: 65 [6400/50000 (14%)]\tLoss: 0.092617, Accuracy: 96.88\n",
      "Train Epoch: 65 [7680/50000 (17%)]\tLoss: 0.066186, Accuracy: 97.66\n",
      "Train Epoch: 65 [8960/50000 (20%)]\tLoss: 0.054830, Accuracy: 98.05\n",
      "Train Epoch: 65 [10240/50000 (23%)]\tLoss: 0.062972, Accuracy: 97.27\n",
      "Train Epoch: 65 [11520/50000 (26%)]\tLoss: 0.056397, Accuracy: 99.22\n",
      "Train Epoch: 65 [12800/50000 (28%)]\tLoss: 0.061942, Accuracy: 97.66\n",
      "Train Epoch: 65 [14080/50000 (31%)]\tLoss: 0.104614, Accuracy: 95.31\n",
      "Train Epoch: 65 [15360/50000 (34%)]\tLoss: 0.061954, Accuracy: 98.44\n",
      "Train Epoch: 65 [16640/50000 (37%)]\tLoss: 0.036737, Accuracy: 99.22\n",
      "Train Epoch: 65 [17920/50000 (40%)]\tLoss: 0.039508, Accuracy: 98.83\n",
      "Train Epoch: 65 [19200/50000 (43%)]\tLoss: 0.045946, Accuracy: 98.05\n",
      "Train Epoch: 65 [20480/50000 (45%)]\tLoss: 0.078482, Accuracy: 96.48\n",
      "Train Epoch: 65 [21760/50000 (48%)]\tLoss: 0.109542, Accuracy: 97.27\n",
      "Train Epoch: 65 [23040/50000 (51%)]\tLoss: 0.024052, Accuracy: 99.61\n",
      "Train Epoch: 65 [24320/50000 (54%)]\tLoss: 0.073834, Accuracy: 97.66\n",
      "Train Epoch: 65 [25600/50000 (57%)]\tLoss: 0.031647, Accuracy: 99.61\n",
      "Train Epoch: 65 [26880/50000 (60%)]\tLoss: 0.067697, Accuracy: 97.66\n",
      "Train Epoch: 65 [28160/50000 (62%)]\tLoss: 0.094809, Accuracy: 97.27\n",
      "Train Epoch: 65 [29440/50000 (65%)]\tLoss: 0.046128, Accuracy: 99.22\n",
      "Train Epoch: 65 [30720/50000 (68%)]\tLoss: 0.112066, Accuracy: 96.09\n",
      "Train Epoch: 65 [32000/50000 (71%)]\tLoss: 0.067995, Accuracy: 96.88\n",
      "Train Epoch: 65 [33280/50000 (74%)]\tLoss: 0.038075, Accuracy: 98.05\n",
      "Train Epoch: 65 [34560/50000 (77%)]\tLoss: 0.095073, Accuracy: 95.70\n",
      "Train Epoch: 65 [35840/50000 (80%)]\tLoss: 0.089146, Accuracy: 97.27\n",
      "Train Epoch: 65 [37120/50000 (82%)]\tLoss: 0.074795, Accuracy: 98.44\n",
      "Train Epoch: 65 [38400/50000 (85%)]\tLoss: 0.046835, Accuracy: 97.66\n",
      "Train Epoch: 65 [39680/50000 (88%)]\tLoss: 0.065508, Accuracy: 96.88\n",
      "Train Epoch: 65 [40960/50000 (91%)]\tLoss: 0.070348, Accuracy: 97.27\n",
      "Train Epoch: 65 [42240/50000 (94%)]\tLoss: 0.075923, Accuracy: 98.44\n",
      "Train Epoch: 65 [43520/50000 (97%)]\tLoss: 0.040293, Accuracy: 98.05\n",
      "Train Epoch: 65 [35000/50000 (99%)]\tLoss: 0.169608, Accuracy: 94.50\n",
      "\n",
      "Validation set: Average loss: 0.4447, Accuracy: 4444/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.34910774230957 s]\n",
      "Train Epoch: 66 [0/50000 (0%)]\tLoss: 0.062499, Accuracy: 97.66\n",
      "Train Epoch: 66 [1280/50000 (3%)]\tLoss: 0.046585, Accuracy: 99.22\n",
      "Train Epoch: 66 [2560/50000 (6%)]\tLoss: 0.056299, Accuracy: 98.44\n",
      "Train Epoch: 66 [3840/50000 (9%)]\tLoss: 0.092506, Accuracy: 96.09\n",
      "Train Epoch: 66 [5120/50000 (11%)]\tLoss: 0.112607, Accuracy: 95.70\n",
      "Train Epoch: 66 [6400/50000 (14%)]\tLoss: 0.077664, Accuracy: 97.27\n",
      "Train Epoch: 66 [7680/50000 (17%)]\tLoss: 0.061767, Accuracy: 98.44\n",
      "Train Epoch: 66 [8960/50000 (20%)]\tLoss: 0.074594, Accuracy: 98.05\n",
      "Train Epoch: 66 [10240/50000 (23%)]\tLoss: 0.045125, Accuracy: 98.05\n",
      "Train Epoch: 66 [11520/50000 (26%)]\tLoss: 0.073531, Accuracy: 97.27\n",
      "Train Epoch: 66 [12800/50000 (28%)]\tLoss: 0.070208, Accuracy: 97.27\n",
      "Train Epoch: 66 [14080/50000 (31%)]\tLoss: 0.061330, Accuracy: 98.05\n",
      "Train Epoch: 66 [15360/50000 (34%)]\tLoss: 0.055215, Accuracy: 98.05\n",
      "Train Epoch: 66 [16640/50000 (37%)]\tLoss: 0.083379, Accuracy: 97.27\n",
      "Train Epoch: 66 [17920/50000 (40%)]\tLoss: 0.069806, Accuracy: 97.66\n",
      "Train Epoch: 66 [19200/50000 (43%)]\tLoss: 0.052181, Accuracy: 98.44\n",
      "Train Epoch: 66 [20480/50000 (45%)]\tLoss: 0.083638, Accuracy: 96.09\n",
      "Train Epoch: 66 [21760/50000 (48%)]\tLoss: 0.037979, Accuracy: 98.44\n",
      "Train Epoch: 66 [23040/50000 (51%)]\tLoss: 0.048668, Accuracy: 98.05\n",
      "Train Epoch: 66 [24320/50000 (54%)]\tLoss: 0.054315, Accuracy: 98.44\n",
      "Train Epoch: 66 [25600/50000 (57%)]\tLoss: 0.076918, Accuracy: 96.48\n",
      "Train Epoch: 66 [26880/50000 (60%)]\tLoss: 0.043240, Accuracy: 98.44\n",
      "Train Epoch: 66 [28160/50000 (62%)]\tLoss: 0.070817, Accuracy: 98.05\n",
      "Train Epoch: 66 [29440/50000 (65%)]\tLoss: 0.073151, Accuracy: 96.88\n",
      "Train Epoch: 66 [30720/50000 (68%)]\tLoss: 0.029165, Accuracy: 98.83\n",
      "Train Epoch: 66 [32000/50000 (71%)]\tLoss: 0.040961, Accuracy: 98.83\n",
      "Train Epoch: 66 [33280/50000 (74%)]\tLoss: 0.099745, Accuracy: 96.09\n",
      "Train Epoch: 66 [34560/50000 (77%)]\tLoss: 0.045770, Accuracy: 98.83\n",
      "Train Epoch: 66 [35840/50000 (80%)]\tLoss: 0.048879, Accuracy: 97.66\n",
      "Train Epoch: 66 [37120/50000 (82%)]\tLoss: 0.082859, Accuracy: 96.09\n",
      "Train Epoch: 66 [38400/50000 (85%)]\tLoss: 0.052551, Accuracy: 98.83\n",
      "Train Epoch: 66 [39680/50000 (88%)]\tLoss: 0.051896, Accuracy: 98.44\n",
      "Train Epoch: 66 [40960/50000 (91%)]\tLoss: 0.098311, Accuracy: 97.27\n",
      "Train Epoch: 66 [42240/50000 (94%)]\tLoss: 0.093115, Accuracy: 97.66\n",
      "Train Epoch: 66 [43520/50000 (97%)]\tLoss: 0.062198, Accuracy: 97.66\n",
      "Train Epoch: 66 [35000/50000 (99%)]\tLoss: 0.126553, Accuracy: 95.50\n",
      "\n",
      "Validation set: Average loss: 0.4437, Accuracy: 4468/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.316550493240356 s]\n",
      "Train Epoch: 67 [0/50000 (0%)]\tLoss: 0.080342, Accuracy: 97.27\n",
      "Train Epoch: 67 [1280/50000 (3%)]\tLoss: 0.047308, Accuracy: 97.66\n",
      "Train Epoch: 67 [2560/50000 (6%)]\tLoss: 0.046632, Accuracy: 98.83\n",
      "Train Epoch: 67 [3840/50000 (9%)]\tLoss: 0.084202, Accuracy: 96.48\n",
      "Train Epoch: 67 [5120/50000 (11%)]\tLoss: 0.031938, Accuracy: 99.22\n",
      "Train Epoch: 67 [6400/50000 (14%)]\tLoss: 0.028030, Accuracy: 100.00\n",
      "Train Epoch: 67 [7680/50000 (17%)]\tLoss: 0.047872, Accuracy: 98.44\n",
      "Train Epoch: 67 [8960/50000 (20%)]\tLoss: 0.121016, Accuracy: 96.09\n",
      "Train Epoch: 67 [10240/50000 (23%)]\tLoss: 0.077721, Accuracy: 97.27\n",
      "Train Epoch: 67 [11520/50000 (26%)]\tLoss: 0.041263, Accuracy: 98.83\n",
      "Train Epoch: 67 [12800/50000 (28%)]\tLoss: 0.055710, Accuracy: 98.44\n",
      "Train Epoch: 67 [14080/50000 (31%)]\tLoss: 0.060151, Accuracy: 98.05\n",
      "Train Epoch: 67 [15360/50000 (34%)]\tLoss: 0.056037, Accuracy: 97.66\n",
      "Train Epoch: 67 [16640/50000 (37%)]\tLoss: 0.045969, Accuracy: 98.05\n",
      "Train Epoch: 67 [17920/50000 (40%)]\tLoss: 0.123006, Accuracy: 95.70\n",
      "Train Epoch: 67 [19200/50000 (43%)]\tLoss: 0.110300, Accuracy: 96.09\n",
      "Train Epoch: 67 [20480/50000 (45%)]\tLoss: 0.076687, Accuracy: 96.88\n",
      "Train Epoch: 67 [21760/50000 (48%)]\tLoss: 0.062626, Accuracy: 97.66\n",
      "Train Epoch: 67 [23040/50000 (51%)]\tLoss: 0.035926, Accuracy: 98.83\n",
      "Train Epoch: 67 [24320/50000 (54%)]\tLoss: 0.044698, Accuracy: 98.44\n",
      "Train Epoch: 67 [25600/50000 (57%)]\tLoss: 0.093005, Accuracy: 96.09\n",
      "Train Epoch: 67 [26880/50000 (60%)]\tLoss: 0.071960, Accuracy: 97.27\n",
      "Train Epoch: 67 [28160/50000 (62%)]\tLoss: 0.068179, Accuracy: 97.27\n",
      "Train Epoch: 67 [29440/50000 (65%)]\tLoss: 0.053622, Accuracy: 97.27\n",
      "Train Epoch: 67 [30720/50000 (68%)]\tLoss: 0.040495, Accuracy: 98.44\n",
      "Train Epoch: 67 [32000/50000 (71%)]\tLoss: 0.085489, Accuracy: 97.27\n",
      "Train Epoch: 67 [33280/50000 (74%)]\tLoss: 0.073014, Accuracy: 97.66\n",
      "Train Epoch: 67 [34560/50000 (77%)]\tLoss: 0.030262, Accuracy: 98.83\n",
      "Train Epoch: 67 [35840/50000 (80%)]\tLoss: 0.033905, Accuracy: 98.83\n",
      "Train Epoch: 67 [37120/50000 (82%)]\tLoss: 0.041914, Accuracy: 98.44\n",
      "Train Epoch: 67 [38400/50000 (85%)]\tLoss: 0.079967, Accuracy: 96.88\n",
      "Train Epoch: 67 [39680/50000 (88%)]\tLoss: 0.060032, Accuracy: 98.44\n",
      "Train Epoch: 67 [40960/50000 (91%)]\tLoss: 0.040061, Accuracy: 99.22\n",
      "Train Epoch: 67 [42240/50000 (94%)]\tLoss: 0.046988, Accuracy: 97.66\n",
      "Train Epoch: 67 [43520/50000 (97%)]\tLoss: 0.084005, Accuracy: 96.09\n",
      "Train Epoch: 67 [35000/50000 (99%)]\tLoss: 0.103978, Accuracy: 95.00\n",
      "\n",
      "Validation set: Average loss: 0.4532, Accuracy: 4444/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.31510639190674 s]\n",
      "Train Epoch: 68 [0/50000 (0%)]\tLoss: 0.067821, Accuracy: 97.66\n",
      "Train Epoch: 68 [1280/50000 (3%)]\tLoss: 0.097970, Accuracy: 96.09\n",
      "Train Epoch: 68 [2560/50000 (6%)]\tLoss: 0.077683, Accuracy: 97.27\n",
      "Train Epoch: 68 [3840/50000 (9%)]\tLoss: 0.075625, Accuracy: 97.66\n",
      "Train Epoch: 68 [5120/50000 (11%)]\tLoss: 0.087733, Accuracy: 97.66\n",
      "Train Epoch: 68 [6400/50000 (14%)]\tLoss: 0.048393, Accuracy: 98.44\n",
      "Train Epoch: 68 [7680/50000 (17%)]\tLoss: 0.079690, Accuracy: 96.88\n",
      "Train Epoch: 68 [8960/50000 (20%)]\tLoss: 0.036223, Accuracy: 98.44\n",
      "Train Epoch: 68 [10240/50000 (23%)]\tLoss: 0.048685, Accuracy: 98.83\n",
      "Train Epoch: 68 [11520/50000 (26%)]\tLoss: 0.062494, Accuracy: 98.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 68 [12800/50000 (28%)]\tLoss: 0.061019, Accuracy: 98.05\n",
      "Train Epoch: 68 [14080/50000 (31%)]\tLoss: 0.071609, Accuracy: 97.66\n",
      "Train Epoch: 68 [15360/50000 (34%)]\tLoss: 0.062898, Accuracy: 97.27\n",
      "Train Epoch: 68 [16640/50000 (37%)]\tLoss: 0.067549, Accuracy: 97.66\n",
      "Train Epoch: 68 [17920/50000 (40%)]\tLoss: 0.076558, Accuracy: 96.88\n",
      "Train Epoch: 68 [19200/50000 (43%)]\tLoss: 0.053912, Accuracy: 98.44\n",
      "Train Epoch: 68 [20480/50000 (45%)]\tLoss: 0.025879, Accuracy: 99.61\n",
      "Train Epoch: 68 [21760/50000 (48%)]\tLoss: 0.034807, Accuracy: 98.44\n",
      "Train Epoch: 68 [23040/50000 (51%)]\tLoss: 0.048023, Accuracy: 98.44\n",
      "Train Epoch: 68 [24320/50000 (54%)]\tLoss: 0.056774, Accuracy: 97.66\n",
      "Train Epoch: 68 [25600/50000 (57%)]\tLoss: 0.058919, Accuracy: 97.66\n",
      "Train Epoch: 68 [26880/50000 (60%)]\tLoss: 0.030867, Accuracy: 98.83\n",
      "Train Epoch: 68 [28160/50000 (62%)]\tLoss: 0.064333, Accuracy: 98.05\n",
      "Train Epoch: 68 [29440/50000 (65%)]\tLoss: 0.067610, Accuracy: 97.27\n",
      "Train Epoch: 68 [30720/50000 (68%)]\tLoss: 0.068410, Accuracy: 97.27\n",
      "Train Epoch: 68 [32000/50000 (71%)]\tLoss: 0.025122, Accuracy: 99.61\n",
      "Train Epoch: 68 [33280/50000 (74%)]\tLoss: 0.029027, Accuracy: 99.61\n",
      "Train Epoch: 68 [34560/50000 (77%)]\tLoss: 0.072482, Accuracy: 97.27\n",
      "Train Epoch: 68 [35840/50000 (80%)]\tLoss: 0.062126, Accuracy: 98.44\n",
      "Train Epoch: 68 [37120/50000 (82%)]\tLoss: 0.071209, Accuracy: 97.27\n",
      "Train Epoch: 68 [38400/50000 (85%)]\tLoss: 0.052310, Accuracy: 98.05\n",
      "Train Epoch: 68 [39680/50000 (88%)]\tLoss: 0.031215, Accuracy: 99.22\n",
      "Train Epoch: 68 [40960/50000 (91%)]\tLoss: 0.070730, Accuracy: 98.44\n",
      "Train Epoch: 68 [42240/50000 (94%)]\tLoss: 0.082622, Accuracy: 96.48\n",
      "Train Epoch: 68 [43520/50000 (97%)]\tLoss: 0.053649, Accuracy: 98.44\n",
      "Train Epoch: 68 [35000/50000 (99%)]\tLoss: 0.074889, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.4577, Accuracy: 4447/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.347760438919067 s]\n",
      "Train Epoch: 69 [0/50000 (0%)]\tLoss: 0.060714, Accuracy: 97.27\n",
      "Train Epoch: 69 [1280/50000 (3%)]\tLoss: 0.056907, Accuracy: 98.05\n",
      "Train Epoch: 69 [2560/50000 (6%)]\tLoss: 0.071780, Accuracy: 97.27\n",
      "Train Epoch: 69 [3840/50000 (9%)]\tLoss: 0.041626, Accuracy: 98.05\n",
      "Train Epoch: 69 [5120/50000 (11%)]\tLoss: 0.089373, Accuracy: 97.27\n",
      "Train Epoch: 69 [6400/50000 (14%)]\tLoss: 0.044768, Accuracy: 98.44\n",
      "Train Epoch: 69 [7680/50000 (17%)]\tLoss: 0.068261, Accuracy: 98.44\n",
      "Train Epoch: 69 [8960/50000 (20%)]\tLoss: 0.029134, Accuracy: 98.83\n",
      "Train Epoch: 69 [10240/50000 (23%)]\tLoss: 0.045791, Accuracy: 98.44\n",
      "Train Epoch: 69 [11520/50000 (26%)]\tLoss: 0.078915, Accuracy: 97.66\n",
      "Train Epoch: 69 [12800/50000 (28%)]\tLoss: 0.070481, Accuracy: 97.27\n",
      "Train Epoch: 69 [14080/50000 (31%)]\tLoss: 0.038228, Accuracy: 98.83\n",
      "Train Epoch: 69 [15360/50000 (34%)]\tLoss: 0.081092, Accuracy: 97.66\n",
      "Train Epoch: 69 [16640/50000 (37%)]\tLoss: 0.053008, Accuracy: 97.66\n",
      "Train Epoch: 69 [17920/50000 (40%)]\tLoss: 0.051959, Accuracy: 98.44\n",
      "Train Epoch: 69 [19200/50000 (43%)]\tLoss: 0.081079, Accuracy: 96.88\n",
      "Train Epoch: 69 [20480/50000 (45%)]\tLoss: 0.057403, Accuracy: 98.44\n",
      "Train Epoch: 69 [21760/50000 (48%)]\tLoss: 0.044604, Accuracy: 97.66\n",
      "Train Epoch: 69 [23040/50000 (51%)]\tLoss: 0.049269, Accuracy: 98.05\n",
      "Train Epoch: 69 [24320/50000 (54%)]\tLoss: 0.050129, Accuracy: 98.05\n",
      "Train Epoch: 69 [25600/50000 (57%)]\tLoss: 0.036780, Accuracy: 98.83\n",
      "Train Epoch: 69 [26880/50000 (60%)]\tLoss: 0.103313, Accuracy: 96.88\n",
      "Train Epoch: 69 [28160/50000 (62%)]\tLoss: 0.045789, Accuracy: 98.44\n",
      "Train Epoch: 69 [29440/50000 (65%)]\tLoss: 0.041236, Accuracy: 98.44\n",
      "Train Epoch: 69 [30720/50000 (68%)]\tLoss: 0.057605, Accuracy: 98.05\n",
      "Train Epoch: 69 [32000/50000 (71%)]\tLoss: 0.057341, Accuracy: 97.66\n",
      "Train Epoch: 69 [33280/50000 (74%)]\tLoss: 0.052028, Accuracy: 98.44\n",
      "Train Epoch: 69 [34560/50000 (77%)]\tLoss: 0.092966, Accuracy: 96.48\n",
      "Train Epoch: 69 [35840/50000 (80%)]\tLoss: 0.074975, Accuracy: 97.66\n",
      "Train Epoch: 69 [37120/50000 (82%)]\tLoss: 0.091952, Accuracy: 97.66\n",
      "Train Epoch: 69 [38400/50000 (85%)]\tLoss: 0.096239, Accuracy: 96.88\n",
      "Train Epoch: 69 [39680/50000 (88%)]\tLoss: 0.096105, Accuracy: 96.48\n",
      "Train Epoch: 69 [40960/50000 (91%)]\tLoss: 0.090854, Accuracy: 97.27\n",
      "Train Epoch: 69 [42240/50000 (94%)]\tLoss: 0.080250, Accuracy: 96.88\n",
      "Train Epoch: 69 [43520/50000 (97%)]\tLoss: 0.091150, Accuracy: 96.88\n",
      "Train Epoch: 69 [35000/50000 (99%)]\tLoss: 0.072130, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.4599, Accuracy: 4456/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.344074726104736 s]\n",
      "Train Epoch: 70 [0/50000 (0%)]\tLoss: 0.072777, Accuracy: 97.66\n",
      "Train Epoch: 70 [1280/50000 (3%)]\tLoss: 0.034233, Accuracy: 98.83\n",
      "Train Epoch: 70 [2560/50000 (6%)]\tLoss: 0.076874, Accuracy: 97.66\n",
      "Train Epoch: 70 [3840/50000 (9%)]\tLoss: 0.024982, Accuracy: 99.61\n",
      "Train Epoch: 70 [5120/50000 (11%)]\tLoss: 0.092448, Accuracy: 97.27\n",
      "Train Epoch: 70 [6400/50000 (14%)]\tLoss: 0.049744, Accuracy: 98.44\n",
      "Train Epoch: 70 [7680/50000 (17%)]\tLoss: 0.057465, Accuracy: 97.66\n",
      "Train Epoch: 70 [8960/50000 (20%)]\tLoss: 0.026541, Accuracy: 99.22\n",
      "Train Epoch: 70 [10240/50000 (23%)]\tLoss: 0.036101, Accuracy: 98.83\n",
      "Train Epoch: 70 [11520/50000 (26%)]\tLoss: 0.051125, Accuracy: 97.66\n",
      "Train Epoch: 70 [12800/50000 (28%)]\tLoss: 0.055893, Accuracy: 98.44\n",
      "Train Epoch: 70 [14080/50000 (31%)]\tLoss: 0.081161, Accuracy: 96.48\n",
      "Train Epoch: 70 [15360/50000 (34%)]\tLoss: 0.053274, Accuracy: 97.66\n",
      "Train Epoch: 70 [16640/50000 (37%)]\tLoss: 0.061665, Accuracy: 98.05\n",
      "Train Epoch: 70 [17920/50000 (40%)]\tLoss: 0.040847, Accuracy: 98.44\n",
      "Train Epoch: 70 [19200/50000 (43%)]\tLoss: 0.113523, Accuracy: 96.48\n",
      "Train Epoch: 70 [20480/50000 (45%)]\tLoss: 0.059372, Accuracy: 97.66\n",
      "Train Epoch: 70 [21760/50000 (48%)]\tLoss: 0.035158, Accuracy: 98.44\n",
      "Train Epoch: 70 [23040/50000 (51%)]\tLoss: 0.109872, Accuracy: 97.27\n",
      "Train Epoch: 70 [24320/50000 (54%)]\tLoss: 0.075275, Accuracy: 96.48\n",
      "Train Epoch: 70 [25600/50000 (57%)]\tLoss: 0.067892, Accuracy: 97.66\n",
      "Train Epoch: 70 [26880/50000 (60%)]\tLoss: 0.126290, Accuracy: 95.70\n",
      "Train Epoch: 70 [28160/50000 (62%)]\tLoss: 0.050516, Accuracy: 97.66\n",
      "Train Epoch: 70 [29440/50000 (65%)]\tLoss: 0.085460, Accuracy: 96.48\n",
      "Train Epoch: 70 [30720/50000 (68%)]\tLoss: 0.082176, Accuracy: 98.05\n",
      "Train Epoch: 70 [32000/50000 (71%)]\tLoss: 0.030174, Accuracy: 98.83\n",
      "Train Epoch: 70 [33280/50000 (74%)]\tLoss: 0.056612, Accuracy: 97.27\n",
      "Train Epoch: 70 [34560/50000 (77%)]\tLoss: 0.029993, Accuracy: 98.83\n",
      "Train Epoch: 70 [35840/50000 (80%)]\tLoss: 0.058417, Accuracy: 97.27\n",
      "Train Epoch: 70 [37120/50000 (82%)]\tLoss: 0.111636, Accuracy: 96.88\n",
      "Train Epoch: 70 [38400/50000 (85%)]\tLoss: 0.021615, Accuracy: 99.61\n",
      "Train Epoch: 70 [39680/50000 (88%)]\tLoss: 0.071683, Accuracy: 96.88\n",
      "Train Epoch: 70 [40960/50000 (91%)]\tLoss: 0.039060, Accuracy: 98.44\n",
      "Train Epoch: 70 [42240/50000 (94%)]\tLoss: 0.115068, Accuracy: 95.70\n",
      "Train Epoch: 70 [43520/50000 (97%)]\tLoss: 0.036287, Accuracy: 98.05\n",
      "Train Epoch: 70 [35000/50000 (99%)]\tLoss: 0.079448, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.4544, Accuracy: 4463/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.32897424697876 s]\n",
      "Train Epoch: 71 [0/50000 (0%)]\tLoss: 0.057939, Accuracy: 97.66\n",
      "Train Epoch: 71 [1280/50000 (3%)]\tLoss: 0.053496, Accuracy: 98.44\n",
      "Train Epoch: 71 [2560/50000 (6%)]\tLoss: 0.030767, Accuracy: 99.22\n",
      "Train Epoch: 71 [3840/50000 (9%)]\tLoss: 0.082615, Accuracy: 97.27\n",
      "Train Epoch: 71 [5120/50000 (11%)]\tLoss: 0.025103, Accuracy: 99.22\n",
      "Train Epoch: 71 [6400/50000 (14%)]\tLoss: 0.102057, Accuracy: 97.66\n",
      "Train Epoch: 71 [7680/50000 (17%)]\tLoss: 0.103197, Accuracy: 96.88\n",
      "Train Epoch: 71 [8960/50000 (20%)]\tLoss: 0.043296, Accuracy: 97.66\n",
      "Train Epoch: 71 [10240/50000 (23%)]\tLoss: 0.093206, Accuracy: 97.27\n",
      "Train Epoch: 71 [11520/50000 (26%)]\tLoss: 0.083579, Accuracy: 98.05\n",
      "Train Epoch: 71 [12800/50000 (28%)]\tLoss: 0.071071, Accuracy: 97.66\n",
      "Train Epoch: 71 [14080/50000 (31%)]\tLoss: 0.039657, Accuracy: 98.05\n",
      "Train Epoch: 71 [15360/50000 (34%)]\tLoss: 0.046928, Accuracy: 98.44\n",
      "Train Epoch: 71 [16640/50000 (37%)]\tLoss: 0.114621, Accuracy: 96.48\n",
      "Train Epoch: 71 [17920/50000 (40%)]\tLoss: 0.020718, Accuracy: 99.22\n",
      "Train Epoch: 71 [19200/50000 (43%)]\tLoss: 0.040503, Accuracy: 98.05\n",
      "Train Epoch: 71 [20480/50000 (45%)]\tLoss: 0.041773, Accuracy: 98.44\n",
      "Train Epoch: 71 [21760/50000 (48%)]\tLoss: 0.121097, Accuracy: 96.09\n",
      "Train Epoch: 71 [23040/50000 (51%)]\tLoss: 0.068388, Accuracy: 97.66\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 71 [24320/50000 (54%)]\tLoss: 0.081072, Accuracy: 97.27\n",
      "Train Epoch: 71 [25600/50000 (57%)]\tLoss: 0.068956, Accuracy: 96.48\n",
      "Train Epoch: 71 [26880/50000 (60%)]\tLoss: 0.082253, Accuracy: 96.88\n",
      "Train Epoch: 71 [28160/50000 (62%)]\tLoss: 0.059046, Accuracy: 98.83\n",
      "Train Epoch: 71 [29440/50000 (65%)]\tLoss: 0.084539, Accuracy: 98.05\n",
      "Train Epoch: 71 [30720/50000 (68%)]\tLoss: 0.022138, Accuracy: 99.22\n",
      "Train Epoch: 71 [32000/50000 (71%)]\tLoss: 0.084792, Accuracy: 98.44\n",
      "Train Epoch: 71 [33280/50000 (74%)]\tLoss: 0.067143, Accuracy: 96.88\n",
      "Train Epoch: 71 [34560/50000 (77%)]\tLoss: 0.028199, Accuracy: 98.44\n",
      "Train Epoch: 71 [35840/50000 (80%)]\tLoss: 0.118911, Accuracy: 96.88\n",
      "Train Epoch: 71 [37120/50000 (82%)]\tLoss: 0.063068, Accuracy: 97.66\n",
      "Train Epoch: 71 [38400/50000 (85%)]\tLoss: 0.034134, Accuracy: 98.05\n",
      "Train Epoch: 71 [39680/50000 (88%)]\tLoss: 0.038733, Accuracy: 98.05\n",
      "Train Epoch: 71 [40960/50000 (91%)]\tLoss: 0.053657, Accuracy: 98.44\n",
      "Train Epoch: 71 [42240/50000 (94%)]\tLoss: 0.023285, Accuracy: 99.22\n",
      "Train Epoch: 71 [43520/50000 (97%)]\tLoss: 0.100702, Accuracy: 96.88\n",
      "Train Epoch: 71 [35000/50000 (99%)]\tLoss: 0.020362, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.4941, Accuracy: 4444/5000 (88.00%)\n",
      "\n",
      "the time of this epoch:[21.309114456176758 s]\n",
      "Train Epoch: 72 [0/50000 (0%)]\tLoss: 0.034336, Accuracy: 98.44\n",
      "Train Epoch: 72 [1280/50000 (3%)]\tLoss: 0.032502, Accuracy: 99.61\n",
      "Train Epoch: 72 [2560/50000 (6%)]\tLoss: 0.050838, Accuracy: 98.44\n",
      "Train Epoch: 72 [3840/50000 (9%)]\tLoss: 0.047488, Accuracy: 98.44\n",
      "Train Epoch: 72 [5120/50000 (11%)]\tLoss: 0.042391, Accuracy: 98.44\n",
      "Train Epoch: 72 [6400/50000 (14%)]\tLoss: 0.046217, Accuracy: 98.83\n",
      "Train Epoch: 72 [7680/50000 (17%)]\tLoss: 0.069285, Accuracy: 97.27\n",
      "Train Epoch: 72 [8960/50000 (20%)]\tLoss: 0.061572, Accuracy: 97.66\n",
      "Train Epoch: 72 [10240/50000 (23%)]\tLoss: 0.060341, Accuracy: 97.66\n",
      "Train Epoch: 72 [11520/50000 (26%)]\tLoss: 0.053375, Accuracy: 98.44\n",
      "Train Epoch: 72 [12800/50000 (28%)]\tLoss: 0.051011, Accuracy: 98.44\n",
      "Train Epoch: 72 [14080/50000 (31%)]\tLoss: 0.064382, Accuracy: 97.66\n",
      "Train Epoch: 72 [15360/50000 (34%)]\tLoss: 0.042798, Accuracy: 97.66\n",
      "Train Epoch: 72 [16640/50000 (37%)]\tLoss: 0.017921, Accuracy: 100.00\n",
      "Train Epoch: 72 [17920/50000 (40%)]\tLoss: 0.051562, Accuracy: 97.27\n",
      "Train Epoch: 72 [19200/50000 (43%)]\tLoss: 0.071156, Accuracy: 96.88\n",
      "Train Epoch: 72 [20480/50000 (45%)]\tLoss: 0.035413, Accuracy: 99.22\n",
      "Train Epoch: 72 [21760/50000 (48%)]\tLoss: 0.072379, Accuracy: 96.88\n",
      "Train Epoch: 72 [23040/50000 (51%)]\tLoss: 0.022332, Accuracy: 99.22\n",
      "Train Epoch: 72 [24320/50000 (54%)]\tLoss: 0.073470, Accuracy: 97.66\n",
      "Train Epoch: 72 [25600/50000 (57%)]\tLoss: 0.043585, Accuracy: 98.44\n",
      "Train Epoch: 72 [26880/50000 (60%)]\tLoss: 0.058186, Accuracy: 97.66\n",
      "Train Epoch: 72 [28160/50000 (62%)]\tLoss: 0.033290, Accuracy: 99.22\n",
      "Train Epoch: 72 [29440/50000 (65%)]\tLoss: 0.070250, Accuracy: 98.44\n",
      "Train Epoch: 72 [30720/50000 (68%)]\tLoss: 0.032255, Accuracy: 99.22\n",
      "Train Epoch: 72 [32000/50000 (71%)]\tLoss: 0.058437, Accuracy: 98.05\n",
      "Train Epoch: 72 [33280/50000 (74%)]\tLoss: 0.080317, Accuracy: 97.66\n",
      "Train Epoch: 72 [34560/50000 (77%)]\tLoss: 0.026169, Accuracy: 99.61\n",
      "Train Epoch: 72 [35840/50000 (80%)]\tLoss: 0.039648, Accuracy: 97.66\n",
      "Train Epoch: 72 [37120/50000 (82%)]\tLoss: 0.053652, Accuracy: 98.05\n",
      "Train Epoch: 72 [38400/50000 (85%)]\tLoss: 0.069955, Accuracy: 98.05\n",
      "Train Epoch: 72 [39680/50000 (88%)]\tLoss: 0.067312, Accuracy: 97.27\n",
      "Train Epoch: 72 [40960/50000 (91%)]\tLoss: 0.064247, Accuracy: 97.66\n",
      "Train Epoch: 72 [42240/50000 (94%)]\tLoss: 0.075021, Accuracy: 97.66\n",
      "Train Epoch: 72 [43520/50000 (97%)]\tLoss: 0.066259, Accuracy: 98.05\n",
      "Train Epoch: 72 [35000/50000 (99%)]\tLoss: 0.063498, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4654, Accuracy: 4450/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.323729038238525 s]\n",
      "Train Epoch: 73 [0/50000 (0%)]\tLoss: 0.033942, Accuracy: 98.44\n",
      "Train Epoch: 73 [1280/50000 (3%)]\tLoss: 0.047595, Accuracy: 98.83\n",
      "Train Epoch: 73 [2560/50000 (6%)]\tLoss: 0.048799, Accuracy: 98.05\n",
      "Train Epoch: 73 [3840/50000 (9%)]\tLoss: 0.037569, Accuracy: 98.83\n",
      "Train Epoch: 73 [5120/50000 (11%)]\tLoss: 0.064486, Accuracy: 97.66\n",
      "Train Epoch: 73 [6400/50000 (14%)]\tLoss: 0.058086, Accuracy: 98.44\n",
      "Train Epoch: 73 [7680/50000 (17%)]\tLoss: 0.076124, Accuracy: 96.88\n",
      "Train Epoch: 73 [8960/50000 (20%)]\tLoss: 0.070512, Accuracy: 96.48\n",
      "Train Epoch: 73 [10240/50000 (23%)]\tLoss: 0.044526, Accuracy: 98.44\n",
      "Train Epoch: 73 [11520/50000 (26%)]\tLoss: 0.032156, Accuracy: 98.83\n",
      "Train Epoch: 73 [12800/50000 (28%)]\tLoss: 0.047452, Accuracy: 98.05\n",
      "Train Epoch: 73 [14080/50000 (31%)]\tLoss: 0.050000, Accuracy: 98.05\n",
      "Train Epoch: 73 [15360/50000 (34%)]\tLoss: 0.044200, Accuracy: 98.44\n",
      "Train Epoch: 73 [16640/50000 (37%)]\tLoss: 0.055386, Accuracy: 98.44\n",
      "Train Epoch: 73 [17920/50000 (40%)]\tLoss: 0.029225, Accuracy: 98.83\n",
      "Train Epoch: 73 [19200/50000 (43%)]\tLoss: 0.049846, Accuracy: 98.05\n",
      "Train Epoch: 73 [20480/50000 (45%)]\tLoss: 0.017220, Accuracy: 100.00\n",
      "Train Epoch: 73 [21760/50000 (48%)]\tLoss: 0.046241, Accuracy: 97.66\n",
      "Train Epoch: 73 [23040/50000 (51%)]\tLoss: 0.033733, Accuracy: 98.44\n",
      "Train Epoch: 73 [24320/50000 (54%)]\tLoss: 0.097059, Accuracy: 96.09\n",
      "Train Epoch: 73 [25600/50000 (57%)]\tLoss: 0.111175, Accuracy: 96.48\n",
      "Train Epoch: 73 [26880/50000 (60%)]\tLoss: 0.039472, Accuracy: 98.83\n",
      "Train Epoch: 73 [28160/50000 (62%)]\tLoss: 0.059954, Accuracy: 98.44\n",
      "Train Epoch: 73 [29440/50000 (65%)]\tLoss: 0.053380, Accuracy: 98.05\n",
      "Train Epoch: 73 [30720/50000 (68%)]\tLoss: 0.034875, Accuracy: 99.22\n",
      "Train Epoch: 73 [32000/50000 (71%)]\tLoss: 0.054206, Accuracy: 97.66\n",
      "Train Epoch: 73 [33280/50000 (74%)]\tLoss: 0.047905, Accuracy: 98.44\n",
      "Train Epoch: 73 [34560/50000 (77%)]\tLoss: 0.095719, Accuracy: 97.27\n",
      "Train Epoch: 73 [35840/50000 (80%)]\tLoss: 0.051401, Accuracy: 97.66\n",
      "Train Epoch: 73 [37120/50000 (82%)]\tLoss: 0.060637, Accuracy: 96.88\n",
      "Train Epoch: 73 [38400/50000 (85%)]\tLoss: 0.065665, Accuracy: 98.05\n",
      "Train Epoch: 73 [39680/50000 (88%)]\tLoss: 0.092375, Accuracy: 96.09\n",
      "Train Epoch: 73 [40960/50000 (91%)]\tLoss: 0.081392, Accuracy: 96.48\n",
      "Train Epoch: 73 [42240/50000 (94%)]\tLoss: 0.037355, Accuracy: 98.83\n",
      "Train Epoch: 73 [43520/50000 (97%)]\tLoss: 0.019812, Accuracy: 99.61\n",
      "Train Epoch: 73 [35000/50000 (99%)]\tLoss: 0.063196, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.4713, Accuracy: 4461/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.32086682319641 s]\n",
      "Train Epoch: 74 [0/50000 (0%)]\tLoss: 0.047797, Accuracy: 98.05\n",
      "Train Epoch: 74 [1280/50000 (3%)]\tLoss: 0.022598, Accuracy: 99.22\n",
      "Train Epoch: 74 [2560/50000 (6%)]\tLoss: 0.036676, Accuracy: 98.83\n",
      "Train Epoch: 74 [3840/50000 (9%)]\tLoss: 0.029661, Accuracy: 98.83\n",
      "Train Epoch: 74 [5120/50000 (11%)]\tLoss: 0.029574, Accuracy: 98.83\n",
      "Train Epoch: 74 [6400/50000 (14%)]\tLoss: 0.040102, Accuracy: 98.44\n",
      "Train Epoch: 74 [7680/50000 (17%)]\tLoss: 0.044599, Accuracy: 98.44\n",
      "Train Epoch: 74 [8960/50000 (20%)]\tLoss: 0.036082, Accuracy: 97.66\n",
      "Train Epoch: 74 [10240/50000 (23%)]\tLoss: 0.058749, Accuracy: 97.27\n",
      "Train Epoch: 74 [11520/50000 (26%)]\tLoss: 0.058754, Accuracy: 98.44\n",
      "Train Epoch: 74 [12800/50000 (28%)]\tLoss: 0.040204, Accuracy: 98.44\n",
      "Train Epoch: 74 [14080/50000 (31%)]\tLoss: 0.085062, Accuracy: 95.31\n",
      "Train Epoch: 74 [15360/50000 (34%)]\tLoss: 0.090412, Accuracy: 95.31\n",
      "Train Epoch: 74 [16640/50000 (37%)]\tLoss: 0.029355, Accuracy: 99.22\n",
      "Train Epoch: 74 [17920/50000 (40%)]\tLoss: 0.050064, Accuracy: 98.05\n",
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      "Train Epoch: 74 [24320/50000 (54%)]\tLoss: 0.070476, Accuracy: 96.09\n",
      "Train Epoch: 74 [25600/50000 (57%)]\tLoss: 0.048995, Accuracy: 98.05\n",
      "Train Epoch: 74 [26880/50000 (60%)]\tLoss: 0.030165, Accuracy: 99.22\n",
      "Train Epoch: 74 [28160/50000 (62%)]\tLoss: 0.041021, Accuracy: 98.83\n",
      "Train Epoch: 74 [29440/50000 (65%)]\tLoss: 0.044520, Accuracy: 99.22\n",
      "Train Epoch: 74 [30720/50000 (68%)]\tLoss: 0.139395, Accuracy: 96.48\n",
      "Train Epoch: 74 [32000/50000 (71%)]\tLoss: 0.048679, Accuracy: 97.66\n",
      "Train Epoch: 74 [33280/50000 (74%)]\tLoss: 0.083654, Accuracy: 97.66\n",
      "Train Epoch: 74 [34560/50000 (77%)]\tLoss: 0.041936, Accuracy: 98.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 74 [35840/50000 (80%)]\tLoss: 0.056486, Accuracy: 98.05\n",
      "Train Epoch: 74 [37120/50000 (82%)]\tLoss: 0.080560, Accuracy: 96.48\n",
      "Train Epoch: 74 [38400/50000 (85%)]\tLoss: 0.033828, Accuracy: 99.22\n",
      "Train Epoch: 74 [39680/50000 (88%)]\tLoss: 0.046898, Accuracy: 98.44\n",
      "Train Epoch: 74 [40960/50000 (91%)]\tLoss: 0.066693, Accuracy: 98.05\n",
      "Train Epoch: 74 [42240/50000 (94%)]\tLoss: 0.041528, Accuracy: 98.05\n",
      "Train Epoch: 74 [43520/50000 (97%)]\tLoss: 0.029422, Accuracy: 98.83\n",
      "Train Epoch: 74 [35000/50000 (99%)]\tLoss: 0.051550, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4652, Accuracy: 4467/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.329355478286743 s]\n",
      "Train Epoch: 75 [0/50000 (0%)]\tLoss: 0.050363, Accuracy: 97.66\n",
      "Train Epoch: 75 [1280/50000 (3%)]\tLoss: 0.014504, Accuracy: 100.00\n",
      "Train Epoch: 75 [2560/50000 (6%)]\tLoss: 0.068719, Accuracy: 98.05\n",
      "Train Epoch: 75 [3840/50000 (9%)]\tLoss: 0.058558, Accuracy: 98.44\n",
      "Train Epoch: 75 [5120/50000 (11%)]\tLoss: 0.032198, Accuracy: 98.44\n",
      "Train Epoch: 75 [6400/50000 (14%)]\tLoss: 0.064659, Accuracy: 97.66\n",
      "Train Epoch: 75 [7680/50000 (17%)]\tLoss: 0.034806, Accuracy: 98.44\n",
      "Train Epoch: 75 [8960/50000 (20%)]\tLoss: 0.049436, Accuracy: 98.44\n",
      "Train Epoch: 75 [10240/50000 (23%)]\tLoss: 0.061888, Accuracy: 97.27\n",
      "Train Epoch: 75 [11520/50000 (26%)]\tLoss: 0.073254, Accuracy: 97.27\n",
      "Train Epoch: 75 [12800/50000 (28%)]\tLoss: 0.086068, Accuracy: 96.48\n",
      "Train Epoch: 75 [14080/50000 (31%)]\tLoss: 0.074717, Accuracy: 98.44\n",
      "Train Epoch: 75 [15360/50000 (34%)]\tLoss: 0.049974, Accuracy: 98.44\n",
      "Train Epoch: 75 [16640/50000 (37%)]\tLoss: 0.046840, Accuracy: 98.83\n",
      "Train Epoch: 75 [17920/50000 (40%)]\tLoss: 0.083673, Accuracy: 98.05\n",
      "Train Epoch: 75 [19200/50000 (43%)]\tLoss: 0.072791, Accuracy: 97.27\n",
      "Train Epoch: 75 [20480/50000 (45%)]\tLoss: 0.042119, Accuracy: 98.44\n",
      "Train Epoch: 75 [21760/50000 (48%)]\tLoss: 0.060348, Accuracy: 97.27\n",
      "Train Epoch: 75 [23040/50000 (51%)]\tLoss: 0.087499, Accuracy: 96.48\n",
      "Train Epoch: 75 [24320/50000 (54%)]\tLoss: 0.046365, Accuracy: 98.83\n",
      "Train Epoch: 75 [25600/50000 (57%)]\tLoss: 0.052583, Accuracy: 98.83\n",
      "Train Epoch: 75 [26880/50000 (60%)]\tLoss: 0.073140, Accuracy: 98.05\n",
      "Train Epoch: 75 [28160/50000 (62%)]\tLoss: 0.054807, Accuracy: 98.05\n",
      "Train Epoch: 75 [29440/50000 (65%)]\tLoss: 0.135044, Accuracy: 96.48\n",
      "Train Epoch: 75 [30720/50000 (68%)]\tLoss: 0.057969, Accuracy: 98.44\n",
      "Train Epoch: 75 [32000/50000 (71%)]\tLoss: 0.081929, Accuracy: 97.27\n",
      "Train Epoch: 75 [33280/50000 (74%)]\tLoss: 0.048770, Accuracy: 98.44\n",
      "Train Epoch: 75 [34560/50000 (77%)]\tLoss: 0.040870, Accuracy: 98.44\n",
      "Train Epoch: 75 [35840/50000 (80%)]\tLoss: 0.072283, Accuracy: 98.05\n",
      "Train Epoch: 75 [37120/50000 (82%)]\tLoss: 0.026071, Accuracy: 99.22\n",
      "Train Epoch: 75 [38400/50000 (85%)]\tLoss: 0.073803, Accuracy: 97.27\n",
      "Train Epoch: 75 [39680/50000 (88%)]\tLoss: 0.018641, Accuracy: 99.22\n",
      "Train Epoch: 75 [40960/50000 (91%)]\tLoss: 0.068479, Accuracy: 97.27\n",
      "Train Epoch: 75 [42240/50000 (94%)]\tLoss: 0.057179, Accuracy: 96.48\n",
      "Train Epoch: 75 [43520/50000 (97%)]\tLoss: 0.043378, Accuracy: 98.44\n",
      "Train Epoch: 75 [35000/50000 (99%)]\tLoss: 0.046993, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.4703, Accuracy: 4453/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.33374261856079 s]\n",
      "Train Epoch: 76 [0/50000 (0%)]\tLoss: 0.027150, Accuracy: 98.83\n",
      "Train Epoch: 76 [1280/50000 (3%)]\tLoss: 0.076463, Accuracy: 96.48\n",
      "Train Epoch: 76 [2560/50000 (6%)]\tLoss: 0.090963, Accuracy: 97.66\n",
      "Train Epoch: 76 [3840/50000 (9%)]\tLoss: 0.046056, Accuracy: 98.83\n",
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      "Train Epoch: 76 [6400/50000 (14%)]\tLoss: 0.042074, Accuracy: 98.83\n",
      "Train Epoch: 76 [7680/50000 (17%)]\tLoss: 0.038675, Accuracy: 98.83\n",
      "Train Epoch: 76 [8960/50000 (20%)]\tLoss: 0.059207, Accuracy: 98.05\n",
      "Train Epoch: 76 [10240/50000 (23%)]\tLoss: 0.034711, Accuracy: 98.44\n",
      "Train Epoch: 76 [11520/50000 (26%)]\tLoss: 0.049914, Accuracy: 98.83\n",
      "Train Epoch: 76 [12800/50000 (28%)]\tLoss: 0.044640, Accuracy: 98.05\n",
      "Train Epoch: 76 [14080/50000 (31%)]\tLoss: 0.087254, Accuracy: 96.48\n",
      "Train Epoch: 76 [15360/50000 (34%)]\tLoss: 0.064594, Accuracy: 97.27\n",
      "Train Epoch: 76 [16640/50000 (37%)]\tLoss: 0.060636, Accuracy: 96.48\n",
      "Train Epoch: 76 [17920/50000 (40%)]\tLoss: 0.082825, Accuracy: 97.66\n",
      "Train Epoch: 76 [19200/50000 (43%)]\tLoss: 0.078090, Accuracy: 96.48\n",
      "Train Epoch: 76 [20480/50000 (45%)]\tLoss: 0.072961, Accuracy: 97.27\n",
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      "Train Epoch: 76 [23040/50000 (51%)]\tLoss: 0.029804, Accuracy: 98.83\n",
      "Train Epoch: 76 [24320/50000 (54%)]\tLoss: 0.027378, Accuracy: 99.22\n",
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      "Train Epoch: 76 [28160/50000 (62%)]\tLoss: 0.042865, Accuracy: 98.05\n",
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      "Train Epoch: 76 [30720/50000 (68%)]\tLoss: 0.041982, Accuracy: 98.83\n",
      "Train Epoch: 76 [32000/50000 (71%)]\tLoss: 0.052205, Accuracy: 97.66\n",
      "Train Epoch: 76 [33280/50000 (74%)]\tLoss: 0.021211, Accuracy: 99.22\n",
      "Train Epoch: 76 [34560/50000 (77%)]\tLoss: 0.099998, Accuracy: 96.09\n",
      "Train Epoch: 76 [35840/50000 (80%)]\tLoss: 0.056799, Accuracy: 96.88\n",
      "Train Epoch: 76 [37120/50000 (82%)]\tLoss: 0.077923, Accuracy: 96.88\n",
      "Train Epoch: 76 [38400/50000 (85%)]\tLoss: 0.103267, Accuracy: 94.92\n",
      "Train Epoch: 76 [39680/50000 (88%)]\tLoss: 0.048981, Accuracy: 98.44\n",
      "Train Epoch: 76 [40960/50000 (91%)]\tLoss: 0.101571, Accuracy: 96.09\n",
      "Train Epoch: 76 [42240/50000 (94%)]\tLoss: 0.054295, Accuracy: 98.44\n",
      "Train Epoch: 76 [43520/50000 (97%)]\tLoss: 0.100060, Accuracy: 95.70\n",
      "Train Epoch: 76 [35000/50000 (99%)]\tLoss: 0.080942, Accuracy: 96.00\n",
      "\n",
      "Validation set: Average loss: 0.4712, Accuracy: 4460/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.355329275131226 s]\n",
      "Train Epoch: 77 [0/50000 (0%)]\tLoss: 0.041917, Accuracy: 98.83\n",
      "Train Epoch: 77 [1280/50000 (3%)]\tLoss: 0.038469, Accuracy: 98.83\n",
      "Train Epoch: 77 [2560/50000 (6%)]\tLoss: 0.074435, Accuracy: 98.05\n",
      "Train Epoch: 77 [3840/50000 (9%)]\tLoss: 0.075681, Accuracy: 97.27\n",
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      "Train Epoch: 77 [11520/50000 (26%)]\tLoss: 0.044945, Accuracy: 97.66\n",
      "Train Epoch: 77 [12800/50000 (28%)]\tLoss: 0.033007, Accuracy: 98.83\n",
      "Train Epoch: 77 [14080/50000 (31%)]\tLoss: 0.041030, Accuracy: 98.44\n",
      "Train Epoch: 77 [15360/50000 (34%)]\tLoss: 0.055052, Accuracy: 98.05\n",
      "Train Epoch: 77 [16640/50000 (37%)]\tLoss: 0.080952, Accuracy: 95.31\n",
      "Train Epoch: 77 [17920/50000 (40%)]\tLoss: 0.056243, Accuracy: 97.27\n",
      "Train Epoch: 77 [19200/50000 (43%)]\tLoss: 0.080095, Accuracy: 96.09\n",
      "Train Epoch: 77 [20480/50000 (45%)]\tLoss: 0.085115, Accuracy: 98.05\n",
      "Train Epoch: 77 [21760/50000 (48%)]\tLoss: 0.106873, Accuracy: 96.48\n",
      "Train Epoch: 77 [23040/50000 (51%)]\tLoss: 0.061422, Accuracy: 97.66\n",
      "Train Epoch: 77 [24320/50000 (54%)]\tLoss: 0.076083, Accuracy: 97.66\n",
      "Train Epoch: 77 [25600/50000 (57%)]\tLoss: 0.056084, Accuracy: 98.05\n",
      "Train Epoch: 77 [26880/50000 (60%)]\tLoss: 0.028102, Accuracy: 98.83\n",
      "Train Epoch: 77 [28160/50000 (62%)]\tLoss: 0.093955, Accuracy: 96.48\n",
      "Train Epoch: 77 [29440/50000 (65%)]\tLoss: 0.058126, Accuracy: 97.66\n",
      "Train Epoch: 77 [30720/50000 (68%)]\tLoss: 0.042265, Accuracy: 97.66\n",
      "Train Epoch: 77 [32000/50000 (71%)]\tLoss: 0.076964, Accuracy: 97.66\n",
      "Train Epoch: 77 [33280/50000 (74%)]\tLoss: 0.074643, Accuracy: 97.27\n",
      "Train Epoch: 77 [34560/50000 (77%)]\tLoss: 0.059729, Accuracy: 98.05\n",
      "Train Epoch: 77 [35840/50000 (80%)]\tLoss: 0.092300, Accuracy: 96.09\n",
      "Train Epoch: 77 [37120/50000 (82%)]\tLoss: 0.085461, Accuracy: 96.48\n",
      "Train Epoch: 77 [38400/50000 (85%)]\tLoss: 0.071615, Accuracy: 96.88\n",
      "Train Epoch: 77 [39680/50000 (88%)]\tLoss: 0.088163, Accuracy: 96.88\n",
      "Train Epoch: 77 [40960/50000 (91%)]\tLoss: 0.029126, Accuracy: 99.22\n",
      "Train Epoch: 77 [42240/50000 (94%)]\tLoss: 0.067929, Accuracy: 96.48\n",
      "Train Epoch: 77 [43520/50000 (97%)]\tLoss: 0.037171, Accuracy: 98.05\n",
      "Train Epoch: 77 [35000/50000 (99%)]\tLoss: 0.043410, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.4765, Accuracy: 4459/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.338069200515747 s]\n",
      "Train Epoch: 78 [0/50000 (0%)]\tLoss: 0.108996, Accuracy: 96.48\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 78 [1280/50000 (3%)]\tLoss: 0.036840, Accuracy: 98.44\n",
      "Train Epoch: 78 [2560/50000 (6%)]\tLoss: 0.053419, Accuracy: 98.05\n",
      "Train Epoch: 78 [3840/50000 (9%)]\tLoss: 0.048208, Accuracy: 98.05\n",
      "Train Epoch: 78 [5120/50000 (11%)]\tLoss: 0.072920, Accuracy: 96.09\n",
      "Train Epoch: 78 [6400/50000 (14%)]\tLoss: 0.033911, Accuracy: 98.05\n",
      "Train Epoch: 78 [7680/50000 (17%)]\tLoss: 0.033609, Accuracy: 99.22\n",
      "Train Epoch: 78 [8960/50000 (20%)]\tLoss: 0.061048, Accuracy: 98.05\n",
      "Train Epoch: 78 [10240/50000 (23%)]\tLoss: 0.078170, Accuracy: 96.48\n",
      "Train Epoch: 78 [11520/50000 (26%)]\tLoss: 0.013262, Accuracy: 99.22\n",
      "Train Epoch: 78 [12800/50000 (28%)]\tLoss: 0.100242, Accuracy: 97.27\n",
      "Train Epoch: 78 [14080/50000 (31%)]\tLoss: 0.048360, Accuracy: 98.44\n",
      "Train Epoch: 78 [15360/50000 (34%)]\tLoss: 0.061530, Accuracy: 97.66\n",
      "Train Epoch: 78 [16640/50000 (37%)]\tLoss: 0.022776, Accuracy: 99.22\n",
      "Train Epoch: 78 [17920/50000 (40%)]\tLoss: 0.040081, Accuracy: 98.83\n",
      "Train Epoch: 78 [19200/50000 (43%)]\tLoss: 0.030540, Accuracy: 99.22\n",
      "Train Epoch: 78 [20480/50000 (45%)]\tLoss: 0.064956, Accuracy: 97.66\n",
      "Train Epoch: 78 [21760/50000 (48%)]\tLoss: 0.059356, Accuracy: 98.05\n",
      "Train Epoch: 78 [23040/50000 (51%)]\tLoss: 0.027818, Accuracy: 99.61\n",
      "Train Epoch: 78 [24320/50000 (54%)]\tLoss: 0.024009, Accuracy: 99.22\n",
      "Train Epoch: 78 [25600/50000 (57%)]\tLoss: 0.075125, Accuracy: 97.27\n",
      "Train Epoch: 78 [26880/50000 (60%)]\tLoss: 0.038724, Accuracy: 98.83\n",
      "Train Epoch: 78 [28160/50000 (62%)]\tLoss: 0.092373, Accuracy: 96.88\n",
      "Train Epoch: 78 [29440/50000 (65%)]\tLoss: 0.022245, Accuracy: 99.22\n",
      "Train Epoch: 78 [30720/50000 (68%)]\tLoss: 0.072344, Accuracy: 97.27\n",
      "Train Epoch: 78 [32000/50000 (71%)]\tLoss: 0.033230, Accuracy: 98.44\n",
      "Train Epoch: 78 [33280/50000 (74%)]\tLoss: 0.048462, Accuracy: 98.44\n",
      "Train Epoch: 78 [34560/50000 (77%)]\tLoss: 0.047440, Accuracy: 97.66\n",
      "Train Epoch: 78 [35840/50000 (80%)]\tLoss: 0.038303, Accuracy: 98.83\n",
      "Train Epoch: 78 [37120/50000 (82%)]\tLoss: 0.031475, Accuracy: 98.05\n",
      "Train Epoch: 78 [38400/50000 (85%)]\tLoss: 0.052046, Accuracy: 98.83\n",
      "Train Epoch: 78 [39680/50000 (88%)]\tLoss: 0.047354, Accuracy: 98.83\n",
      "Train Epoch: 78 [40960/50000 (91%)]\tLoss: 0.029644, Accuracy: 98.44\n",
      "Train Epoch: 78 [42240/50000 (94%)]\tLoss: 0.129525, Accuracy: 96.48\n",
      "Train Epoch: 78 [43520/50000 (97%)]\tLoss: 0.059511, Accuracy: 98.44\n",
      "Train Epoch: 78 [35000/50000 (99%)]\tLoss: 0.037885, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4665, Accuracy: 4466/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.36359143257141 s]\n",
      "Train Epoch: 79 [0/50000 (0%)]\tLoss: 0.069219, Accuracy: 97.66\n",
      "Train Epoch: 79 [1280/50000 (3%)]\tLoss: 0.040812, Accuracy: 98.44\n",
      "Train Epoch: 79 [2560/50000 (6%)]\tLoss: 0.019095, Accuracy: 99.22\n",
      "Train Epoch: 79 [3840/50000 (9%)]\tLoss: 0.027843, Accuracy: 98.44\n",
      "Train Epoch: 79 [5120/50000 (11%)]\tLoss: 0.022806, Accuracy: 99.61\n",
      "Train Epoch: 79 [6400/50000 (14%)]\tLoss: 0.066397, Accuracy: 98.44\n",
      "Train Epoch: 79 [7680/50000 (17%)]\tLoss: 0.058814, Accuracy: 97.27\n",
      "Train Epoch: 79 [8960/50000 (20%)]\tLoss: 0.058831, Accuracy: 98.44\n",
      "Train Epoch: 79 [10240/50000 (23%)]\tLoss: 0.036337, Accuracy: 98.05\n",
      "Train Epoch: 79 [11520/50000 (26%)]\tLoss: 0.023635, Accuracy: 99.22\n",
      "Train Epoch: 79 [12800/50000 (28%)]\tLoss: 0.042543, Accuracy: 97.66\n",
      "Train Epoch: 79 [14080/50000 (31%)]\tLoss: 0.040362, Accuracy: 98.83\n",
      "Train Epoch: 79 [15360/50000 (34%)]\tLoss: 0.049061, Accuracy: 98.44\n",
      "Train Epoch: 79 [16640/50000 (37%)]\tLoss: 0.031216, Accuracy: 99.22\n",
      "Train Epoch: 79 [17920/50000 (40%)]\tLoss: 0.048391, Accuracy: 98.44\n",
      "Train Epoch: 79 [19200/50000 (43%)]\tLoss: 0.068875, Accuracy: 98.05\n",
      "Train Epoch: 79 [20480/50000 (45%)]\tLoss: 0.054138, Accuracy: 98.05\n",
      "Train Epoch: 79 [21760/50000 (48%)]\tLoss: 0.027866, Accuracy: 98.83\n",
      "Train Epoch: 79 [23040/50000 (51%)]\tLoss: 0.106207, Accuracy: 96.88\n",
      "Train Epoch: 79 [24320/50000 (54%)]\tLoss: 0.044481, Accuracy: 98.05\n",
      "Train Epoch: 79 [25600/50000 (57%)]\tLoss: 0.039714, Accuracy: 98.05\n",
      "Train Epoch: 79 [26880/50000 (60%)]\tLoss: 0.059030, Accuracy: 97.66\n",
      "Train Epoch: 79 [28160/50000 (62%)]\tLoss: 0.054490, Accuracy: 97.66\n",
      "Train Epoch: 79 [29440/50000 (65%)]\tLoss: 0.041934, Accuracy: 98.44\n",
      "Train Epoch: 79 [30720/50000 (68%)]\tLoss: 0.046701, Accuracy: 98.83\n",
      "Train Epoch: 79 [32000/50000 (71%)]\tLoss: 0.039954, Accuracy: 98.83\n",
      "Train Epoch: 79 [33280/50000 (74%)]\tLoss: 0.042178, Accuracy: 98.44\n",
      "Train Epoch: 79 [34560/50000 (77%)]\tLoss: 0.038737, Accuracy: 98.83\n",
      "Train Epoch: 79 [35840/50000 (80%)]\tLoss: 0.101278, Accuracy: 96.48\n",
      "Train Epoch: 79 [37120/50000 (82%)]\tLoss: 0.036477, Accuracy: 98.44\n",
      "Train Epoch: 79 [38400/50000 (85%)]\tLoss: 0.030550, Accuracy: 99.22\n",
      "Train Epoch: 79 [39680/50000 (88%)]\tLoss: 0.052723, Accuracy: 97.66\n",
      "Train Epoch: 79 [40960/50000 (91%)]\tLoss: 0.081349, Accuracy: 96.88\n",
      "Train Epoch: 79 [42240/50000 (94%)]\tLoss: 0.047229, Accuracy: 98.44\n",
      "Train Epoch: 79 [43520/50000 (97%)]\tLoss: 0.037520, Accuracy: 98.83\n",
      "Train Epoch: 79 [35000/50000 (99%)]\tLoss: 0.038445, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4843, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.346229076385498 s]\n",
      "Train Epoch: 80 [0/50000 (0%)]\tLoss: 0.068746, Accuracy: 96.88\n",
      "Train Epoch: 80 [1280/50000 (3%)]\tLoss: 0.108887, Accuracy: 96.88\n",
      "Train Epoch: 80 [2560/50000 (6%)]\tLoss: 0.016832, Accuracy: 99.61\n",
      "Train Epoch: 80 [3840/50000 (9%)]\tLoss: 0.032727, Accuracy: 98.83\n",
      "Train Epoch: 80 [5120/50000 (11%)]\tLoss: 0.042642, Accuracy: 98.44\n",
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      "Train Epoch: 80 [11520/50000 (26%)]\tLoss: 0.034702, Accuracy: 98.44\n",
      "Train Epoch: 80 [12800/50000 (28%)]\tLoss: 0.025725, Accuracy: 99.22\n",
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      "Train Epoch: 80 [15360/50000 (34%)]\tLoss: 0.045111, Accuracy: 98.44\n",
      "Train Epoch: 80 [16640/50000 (37%)]\tLoss: 0.122580, Accuracy: 94.53\n",
      "Train Epoch: 80 [17920/50000 (40%)]\tLoss: 0.046075, Accuracy: 98.05\n",
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      "Train Epoch: 80 [21760/50000 (48%)]\tLoss: 0.059863, Accuracy: 98.05\n",
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      "Train Epoch: 80 [28160/50000 (62%)]\tLoss: 0.091769, Accuracy: 97.27\n",
      "Train Epoch: 80 [29440/50000 (65%)]\tLoss: 0.037995, Accuracy: 97.66\n",
      "Train Epoch: 80 [30720/50000 (68%)]\tLoss: 0.069517, Accuracy: 97.27\n",
      "Train Epoch: 80 [32000/50000 (71%)]\tLoss: 0.055448, Accuracy: 98.05\n",
      "Train Epoch: 80 [33280/50000 (74%)]\tLoss: 0.041330, Accuracy: 98.44\n",
      "Train Epoch: 80 [34560/50000 (77%)]\tLoss: 0.078358, Accuracy: 97.27\n",
      "Train Epoch: 80 [35840/50000 (80%)]\tLoss: 0.023195, Accuracy: 99.61\n",
      "Train Epoch: 80 [37120/50000 (82%)]\tLoss: 0.101283, Accuracy: 97.27\n",
      "Train Epoch: 80 [38400/50000 (85%)]\tLoss: 0.027433, Accuracy: 98.44\n",
      "Train Epoch: 80 [39680/50000 (88%)]\tLoss: 0.063853, Accuracy: 96.88\n",
      "Train Epoch: 80 [40960/50000 (91%)]\tLoss: 0.065531, Accuracy: 98.83\n",
      "Train Epoch: 80 [42240/50000 (94%)]\tLoss: 0.075767, Accuracy: 98.05\n",
      "Train Epoch: 80 [43520/50000 (97%)]\tLoss: 0.070692, Accuracy: 97.66\n",
      "Train Epoch: 80 [35000/50000 (99%)]\tLoss: 0.035749, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.4858, Accuracy: 4462/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.354133129119873 s]\n",
      "Train Epoch: 81 [0/50000 (0%)]\tLoss: 0.053167, Accuracy: 98.05\n",
      "Train Epoch: 81 [1280/50000 (3%)]\tLoss: 0.070086, Accuracy: 97.27\n",
      "Train Epoch: 81 [2560/50000 (6%)]\tLoss: 0.040153, Accuracy: 98.44\n",
      "Train Epoch: 81 [3840/50000 (9%)]\tLoss: 0.048998, Accuracy: 97.27\n",
      "Train Epoch: 81 [5120/50000 (11%)]\tLoss: 0.076136, Accuracy: 97.66\n",
      "Train Epoch: 81 [6400/50000 (14%)]\tLoss: 0.078975, Accuracy: 96.09\n",
      "Train Epoch: 81 [7680/50000 (17%)]\tLoss: 0.075571, Accuracy: 97.66\n",
      "Train Epoch: 81 [8960/50000 (20%)]\tLoss: 0.072097, Accuracy: 97.66\n",
      "Train Epoch: 81 [10240/50000 (23%)]\tLoss: 0.025873, Accuracy: 98.83\n",
      "Train Epoch: 81 [11520/50000 (26%)]\tLoss: 0.087751, Accuracy: 96.48\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 81 [12800/50000 (28%)]\tLoss: 0.026297, Accuracy: 98.83\n",
      "Train Epoch: 81 [14080/50000 (31%)]\tLoss: 0.051022, Accuracy: 98.44\n",
      "Train Epoch: 81 [15360/50000 (34%)]\tLoss: 0.047478, Accuracy: 98.44\n",
      "Train Epoch: 81 [16640/50000 (37%)]\tLoss: 0.032544, Accuracy: 98.44\n",
      "Train Epoch: 81 [17920/50000 (40%)]\tLoss: 0.030268, Accuracy: 99.22\n",
      "Train Epoch: 81 [19200/50000 (43%)]\tLoss: 0.030300, Accuracy: 98.83\n",
      "Train Epoch: 81 [20480/50000 (45%)]\tLoss: 0.038702, Accuracy: 97.66\n",
      "Train Epoch: 81 [21760/50000 (48%)]\tLoss: 0.072926, Accuracy: 97.66\n",
      "Train Epoch: 81 [23040/50000 (51%)]\tLoss: 0.031309, Accuracy: 98.83\n",
      "Train Epoch: 81 [24320/50000 (54%)]\tLoss: 0.022300, Accuracy: 99.22\n",
      "Train Epoch: 81 [25600/50000 (57%)]\tLoss: 0.060520, Accuracy: 98.05\n",
      "Train Epoch: 81 [26880/50000 (60%)]\tLoss: 0.041067, Accuracy: 98.44\n",
      "Train Epoch: 81 [28160/50000 (62%)]\tLoss: 0.037073, Accuracy: 98.05\n",
      "Train Epoch: 81 [29440/50000 (65%)]\tLoss: 0.020595, Accuracy: 98.83\n",
      "Train Epoch: 81 [30720/50000 (68%)]\tLoss: 0.072742, Accuracy: 96.09\n",
      "Train Epoch: 81 [32000/50000 (71%)]\tLoss: 0.059043, Accuracy: 97.66\n",
      "Train Epoch: 81 [33280/50000 (74%)]\tLoss: 0.032701, Accuracy: 98.83\n",
      "Train Epoch: 81 [34560/50000 (77%)]\tLoss: 0.044756, Accuracy: 98.44\n",
      "Train Epoch: 81 [35840/50000 (80%)]\tLoss: 0.081057, Accuracy: 97.66\n",
      "Train Epoch: 81 [37120/50000 (82%)]\tLoss: 0.050593, Accuracy: 98.05\n",
      "Train Epoch: 81 [38400/50000 (85%)]\tLoss: 0.052483, Accuracy: 98.44\n",
      "Train Epoch: 81 [39680/50000 (88%)]\tLoss: 0.019060, Accuracy: 99.61\n",
      "Train Epoch: 81 [40960/50000 (91%)]\tLoss: 0.067344, Accuracy: 96.48\n",
      "Train Epoch: 81 [42240/50000 (94%)]\tLoss: 0.020152, Accuracy: 99.22\n",
      "Train Epoch: 81 [43520/50000 (97%)]\tLoss: 0.028320, Accuracy: 98.83\n",
      "Train Epoch: 81 [35000/50000 (99%)]\tLoss: 0.073905, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.4856, Accuracy: 4458/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.325968980789185 s]\n",
      "Train Epoch: 82 [0/50000 (0%)]\tLoss: 0.041234, Accuracy: 98.44\n",
      "Train Epoch: 82 [1280/50000 (3%)]\tLoss: 0.074948, Accuracy: 97.27\n",
      "Train Epoch: 82 [2560/50000 (6%)]\tLoss: 0.059565, Accuracy: 96.88\n",
      "Train Epoch: 82 [3840/50000 (9%)]\tLoss: 0.101271, Accuracy: 96.48\n",
      "Train Epoch: 82 [5120/50000 (11%)]\tLoss: 0.047449, Accuracy: 98.05\n",
      "Train Epoch: 82 [6400/50000 (14%)]\tLoss: 0.042497, Accuracy: 98.83\n",
      "Train Epoch: 82 [7680/50000 (17%)]\tLoss: 0.036951, Accuracy: 98.83\n",
      "Train Epoch: 82 [8960/50000 (20%)]\tLoss: 0.040906, Accuracy: 99.22\n",
      "Train Epoch: 82 [10240/50000 (23%)]\tLoss: 0.072988, Accuracy: 97.66\n",
      "Train Epoch: 82 [11520/50000 (26%)]\tLoss: 0.065057, Accuracy: 96.88\n",
      "Train Epoch: 82 [12800/50000 (28%)]\tLoss: 0.027696, Accuracy: 99.61\n",
      "Train Epoch: 82 [14080/50000 (31%)]\tLoss: 0.095528, Accuracy: 96.48\n",
      "Train Epoch: 82 [15360/50000 (34%)]\tLoss: 0.023414, Accuracy: 99.22\n",
      "Train Epoch: 82 [16640/50000 (37%)]\tLoss: 0.027492, Accuracy: 98.83\n",
      "Train Epoch: 82 [17920/50000 (40%)]\tLoss: 0.076983, Accuracy: 97.27\n",
      "Train Epoch: 82 [19200/50000 (43%)]\tLoss: 0.048149, Accuracy: 98.44\n",
      "Train Epoch: 82 [20480/50000 (45%)]\tLoss: 0.052090, Accuracy: 98.44\n",
      "Train Epoch: 82 [21760/50000 (48%)]\tLoss: 0.081986, Accuracy: 96.09\n",
      "Train Epoch: 82 [23040/50000 (51%)]\tLoss: 0.016305, Accuracy: 99.61\n",
      "Train Epoch: 82 [24320/50000 (54%)]\tLoss: 0.117772, Accuracy: 96.88\n",
      "Train Epoch: 82 [25600/50000 (57%)]\tLoss: 0.070177, Accuracy: 98.05\n",
      "Train Epoch: 82 [26880/50000 (60%)]\tLoss: 0.044611, Accuracy: 98.83\n",
      "Train Epoch: 82 [28160/50000 (62%)]\tLoss: 0.040326, Accuracy: 98.83\n",
      "Train Epoch: 82 [29440/50000 (65%)]\tLoss: 0.025046, Accuracy: 99.22\n",
      "Train Epoch: 82 [30720/50000 (68%)]\tLoss: 0.039155, Accuracy: 99.22\n",
      "Train Epoch: 82 [32000/50000 (71%)]\tLoss: 0.051351, Accuracy: 97.66\n",
      "Train Epoch: 82 [33280/50000 (74%)]\tLoss: 0.057808, Accuracy: 97.27\n",
      "Train Epoch: 82 [34560/50000 (77%)]\tLoss: 0.056031, Accuracy: 98.44\n",
      "Train Epoch: 82 [35840/50000 (80%)]\tLoss: 0.021116, Accuracy: 98.83\n",
      "Train Epoch: 82 [37120/50000 (82%)]\tLoss: 0.014956, Accuracy: 99.61\n",
      "Train Epoch: 82 [38400/50000 (85%)]\tLoss: 0.033098, Accuracy: 99.22\n",
      "Train Epoch: 82 [39680/50000 (88%)]\tLoss: 0.044084, Accuracy: 98.44\n",
      "Train Epoch: 82 [40960/50000 (91%)]\tLoss: 0.017563, Accuracy: 99.61\n",
      "Train Epoch: 82 [42240/50000 (94%)]\tLoss: 0.022695, Accuracy: 99.22\n",
      "Train Epoch: 82 [43520/50000 (97%)]\tLoss: 0.032778, Accuracy: 98.83\n",
      "Train Epoch: 82 [35000/50000 (99%)]\tLoss: 0.031800, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4809, Accuracy: 4456/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.325021266937256 s]\n",
      "Train Epoch: 83 [0/50000 (0%)]\tLoss: 0.101932, Accuracy: 97.27\n",
      "Train Epoch: 83 [1280/50000 (3%)]\tLoss: 0.030629, Accuracy: 98.83\n",
      "Train Epoch: 83 [2560/50000 (6%)]\tLoss: 0.031709, Accuracy: 98.83\n",
      "Train Epoch: 83 [3840/50000 (9%)]\tLoss: 0.031774, Accuracy: 98.83\n",
      "Train Epoch: 83 [5120/50000 (11%)]\tLoss: 0.049241, Accuracy: 98.44\n",
      "Train Epoch: 83 [6400/50000 (14%)]\tLoss: 0.031997, Accuracy: 99.22\n",
      "Train Epoch: 83 [7680/50000 (17%)]\tLoss: 0.023708, Accuracy: 98.83\n",
      "Train Epoch: 83 [8960/50000 (20%)]\tLoss: 0.042646, Accuracy: 99.22\n",
      "Train Epoch: 83 [10240/50000 (23%)]\tLoss: 0.031515, Accuracy: 98.83\n",
      "Train Epoch: 83 [11520/50000 (26%)]\tLoss: 0.017058, Accuracy: 99.61\n",
      "Train Epoch: 83 [12800/50000 (28%)]\tLoss: 0.059310, Accuracy: 98.44\n",
      "Train Epoch: 83 [14080/50000 (31%)]\tLoss: 0.076991, Accuracy: 96.88\n",
      "Train Epoch: 83 [15360/50000 (34%)]\tLoss: 0.023882, Accuracy: 99.22\n",
      "Train Epoch: 83 [16640/50000 (37%)]\tLoss: 0.055304, Accuracy: 98.44\n",
      "Train Epoch: 83 [17920/50000 (40%)]\tLoss: 0.032568, Accuracy: 98.83\n",
      "Train Epoch: 83 [19200/50000 (43%)]\tLoss: 0.037505, Accuracy: 98.83\n",
      "Train Epoch: 83 [20480/50000 (45%)]\tLoss: 0.076424, Accuracy: 97.66\n",
      "Train Epoch: 83 [21760/50000 (48%)]\tLoss: 0.014608, Accuracy: 100.00\n",
      "Train Epoch: 83 [23040/50000 (51%)]\tLoss: 0.053196, Accuracy: 98.05\n",
      "Train Epoch: 83 [24320/50000 (54%)]\tLoss: 0.028922, Accuracy: 99.22\n",
      "Train Epoch: 83 [25600/50000 (57%)]\tLoss: 0.059194, Accuracy: 98.05\n",
      "Train Epoch: 83 [26880/50000 (60%)]\tLoss: 0.035929, Accuracy: 98.44\n",
      "Train Epoch: 83 [28160/50000 (62%)]\tLoss: 0.014966, Accuracy: 99.22\n",
      "Train Epoch: 83 [29440/50000 (65%)]\tLoss: 0.037836, Accuracy: 98.83\n",
      "Train Epoch: 83 [30720/50000 (68%)]\tLoss: 0.102822, Accuracy: 96.48\n",
      "Train Epoch: 83 [32000/50000 (71%)]\tLoss: 0.042516, Accuracy: 99.22\n",
      "Train Epoch: 83 [33280/50000 (74%)]\tLoss: 0.056360, Accuracy: 97.66\n",
      "Train Epoch: 83 [34560/50000 (77%)]\tLoss: 0.049468, Accuracy: 98.44\n",
      "Train Epoch: 83 [35840/50000 (80%)]\tLoss: 0.058170, Accuracy: 98.44\n",
      "Train Epoch: 83 [37120/50000 (82%)]\tLoss: 0.021779, Accuracy: 99.22\n",
      "Train Epoch: 83 [38400/50000 (85%)]\tLoss: 0.036138, Accuracy: 98.44\n",
      "Train Epoch: 83 [39680/50000 (88%)]\tLoss: 0.022409, Accuracy: 99.22\n",
      "Train Epoch: 83 [40960/50000 (91%)]\tLoss: 0.042088, Accuracy: 98.05\n",
      "Train Epoch: 83 [42240/50000 (94%)]\tLoss: 0.028767, Accuracy: 99.61\n",
      "Train Epoch: 83 [43520/50000 (97%)]\tLoss: 0.025165, Accuracy: 99.22\n",
      "Train Epoch: 83 [35000/50000 (99%)]\tLoss: 0.029653, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.4830, Accuracy: 4469/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.32831072807312 s]\n",
      "Train Epoch: 84 [0/50000 (0%)]\tLoss: 0.057457, Accuracy: 98.05\n",
      "Train Epoch: 84 [1280/50000 (3%)]\tLoss: 0.045318, Accuracy: 97.66\n",
      "Train Epoch: 84 [2560/50000 (6%)]\tLoss: 0.034884, Accuracy: 98.44\n",
      "Train Epoch: 84 [3840/50000 (9%)]\tLoss: 0.046299, Accuracy: 98.83\n",
      "Train Epoch: 84 [5120/50000 (11%)]\tLoss: 0.026564, Accuracy: 99.22\n",
      "Train Epoch: 84 [6400/50000 (14%)]\tLoss: 0.056078, Accuracy: 97.66\n",
      "Train Epoch: 84 [7680/50000 (17%)]\tLoss: 0.034534, Accuracy: 98.05\n",
      "Train Epoch: 84 [8960/50000 (20%)]\tLoss: 0.042126, Accuracy: 98.05\n",
      "Train Epoch: 84 [10240/50000 (23%)]\tLoss: 0.041408, Accuracy: 98.44\n",
      "Train Epoch: 84 [11520/50000 (26%)]\tLoss: 0.055957, Accuracy: 98.05\n",
      "Train Epoch: 84 [12800/50000 (28%)]\tLoss: 0.063433, Accuracy: 97.66\n",
      "Train Epoch: 84 [14080/50000 (31%)]\tLoss: 0.027513, Accuracy: 98.83\n",
      "Train Epoch: 84 [15360/50000 (34%)]\tLoss: 0.052775, Accuracy: 97.66\n",
      "Train Epoch: 84 [16640/50000 (37%)]\tLoss: 0.022330, Accuracy: 99.61\n",
      "Train Epoch: 84 [17920/50000 (40%)]\tLoss: 0.061376, Accuracy: 98.05\n",
      "Train Epoch: 84 [19200/50000 (43%)]\tLoss: 0.033073, Accuracy: 99.22\n",
      "Train Epoch: 84 [20480/50000 (45%)]\tLoss: 0.047228, Accuracy: 98.05\n",
      "Train Epoch: 84 [21760/50000 (48%)]\tLoss: 0.028625, Accuracy: 98.83\n",
      "Train Epoch: 84 [23040/50000 (51%)]\tLoss: 0.065684, Accuracy: 97.66\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 84 [24320/50000 (54%)]\tLoss: 0.013745, Accuracy: 99.61\n",
      "Train Epoch: 84 [25600/50000 (57%)]\tLoss: 0.035851, Accuracy: 98.44\n",
      "Train Epoch: 84 [26880/50000 (60%)]\tLoss: 0.039362, Accuracy: 98.05\n",
      "Train Epoch: 84 [28160/50000 (62%)]\tLoss: 0.039932, Accuracy: 97.66\n",
      "Train Epoch: 84 [29440/50000 (65%)]\tLoss: 0.029839, Accuracy: 98.83\n",
      "Train Epoch: 84 [30720/50000 (68%)]\tLoss: 0.058069, Accuracy: 98.44\n",
      "Train Epoch: 84 [32000/50000 (71%)]\tLoss: 0.059193, Accuracy: 97.66\n",
      "Train Epoch: 84 [33280/50000 (74%)]\tLoss: 0.022945, Accuracy: 99.22\n",
      "Train Epoch: 84 [34560/50000 (77%)]\tLoss: 0.030402, Accuracy: 98.83\n",
      "Train Epoch: 84 [35840/50000 (80%)]\tLoss: 0.025175, Accuracy: 99.22\n",
      "Train Epoch: 84 [37120/50000 (82%)]\tLoss: 0.023099, Accuracy: 98.83\n",
      "Train Epoch: 84 [38400/50000 (85%)]\tLoss: 0.033191, Accuracy: 98.44\n",
      "Train Epoch: 84 [39680/50000 (88%)]\tLoss: 0.066786, Accuracy: 98.83\n",
      "Train Epoch: 84 [40960/50000 (91%)]\tLoss: 0.028347, Accuracy: 98.83\n",
      "Train Epoch: 84 [42240/50000 (94%)]\tLoss: 0.026866, Accuracy: 98.83\n",
      "Train Epoch: 84 [43520/50000 (97%)]\tLoss: 0.037789, Accuracy: 98.44\n",
      "Train Epoch: 84 [35000/50000 (99%)]\tLoss: 0.032679, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.4885, Accuracy: 4456/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.38418459892273 s]\n",
      "Train Epoch: 85 [0/50000 (0%)]\tLoss: 0.083643, Accuracy: 97.27\n",
      "Train Epoch: 85 [1280/50000 (3%)]\tLoss: 0.061185, Accuracy: 98.44\n",
      "Train Epoch: 85 [2560/50000 (6%)]\tLoss: 0.032289, Accuracy: 99.61\n",
      "Train Epoch: 85 [3840/50000 (9%)]\tLoss: 0.041684, Accuracy: 98.83\n",
      "Train Epoch: 85 [5120/50000 (11%)]\tLoss: 0.025350, Accuracy: 98.83\n",
      "Train Epoch: 85 [6400/50000 (14%)]\tLoss: 0.035582, Accuracy: 99.22\n",
      "Train Epoch: 85 [7680/50000 (17%)]\tLoss: 0.083237, Accuracy: 97.27\n",
      "Train Epoch: 85 [8960/50000 (20%)]\tLoss: 0.022549, Accuracy: 98.83\n",
      "Train Epoch: 85 [10240/50000 (23%)]\tLoss: 0.029032, Accuracy: 98.83\n",
      "Train Epoch: 85 [11520/50000 (26%)]\tLoss: 0.037381, Accuracy: 98.44\n",
      "Train Epoch: 85 [12800/50000 (28%)]\tLoss: 0.037711, Accuracy: 98.44\n",
      "Train Epoch: 85 [14080/50000 (31%)]\tLoss: 0.041925, Accuracy: 98.83\n",
      "Train Epoch: 85 [15360/50000 (34%)]\tLoss: 0.055822, Accuracy: 98.05\n",
      "Train Epoch: 85 [16640/50000 (37%)]\tLoss: 0.035670, Accuracy: 98.44\n",
      "Train Epoch: 85 [17920/50000 (40%)]\tLoss: 0.057578, Accuracy: 98.05\n",
      "Train Epoch: 85 [19200/50000 (43%)]\tLoss: 0.066875, Accuracy: 96.48\n",
      "Train Epoch: 85 [20480/50000 (45%)]\tLoss: 0.046936, Accuracy: 98.05\n",
      "Train Epoch: 85 [21760/50000 (48%)]\tLoss: 0.043660, Accuracy: 98.83\n",
      "Train Epoch: 85 [23040/50000 (51%)]\tLoss: 0.026586, Accuracy: 98.83\n",
      "Train Epoch: 85 [24320/50000 (54%)]\tLoss: 0.042426, Accuracy: 98.05\n",
      "Train Epoch: 85 [25600/50000 (57%)]\tLoss: 0.018152, Accuracy: 99.61\n",
      "Train Epoch: 85 [26880/50000 (60%)]\tLoss: 0.043990, Accuracy: 98.44\n",
      "Train Epoch: 85 [28160/50000 (62%)]\tLoss: 0.033255, Accuracy: 99.22\n",
      "Train Epoch: 85 [29440/50000 (65%)]\tLoss: 0.068401, Accuracy: 97.66\n",
      "Train Epoch: 85 [30720/50000 (68%)]\tLoss: 0.035938, Accuracy: 99.22\n",
      "Train Epoch: 85 [32000/50000 (71%)]\tLoss: 0.076873, Accuracy: 98.05\n",
      "Train Epoch: 85 [33280/50000 (74%)]\tLoss: 0.061697, Accuracy: 98.05\n",
      "Train Epoch: 85 [34560/50000 (77%)]\tLoss: 0.030182, Accuracy: 98.83\n",
      "Train Epoch: 85 [35840/50000 (80%)]\tLoss: 0.058511, Accuracy: 98.05\n",
      "Train Epoch: 85 [37120/50000 (82%)]\tLoss: 0.056680, Accuracy: 98.05\n",
      "Train Epoch: 85 [38400/50000 (85%)]\tLoss: 0.036289, Accuracy: 98.83\n",
      "Train Epoch: 85 [39680/50000 (88%)]\tLoss: 0.030739, Accuracy: 99.22\n",
      "Train Epoch: 85 [40960/50000 (91%)]\tLoss: 0.043609, Accuracy: 97.66\n",
      "Train Epoch: 85 [42240/50000 (94%)]\tLoss: 0.037247, Accuracy: 98.05\n",
      "Train Epoch: 85 [43520/50000 (97%)]\tLoss: 0.030677, Accuracy: 98.83\n",
      "Train Epoch: 85 [35000/50000 (99%)]\tLoss: 0.062599, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.4802, Accuracy: 4485/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.36150574684143 s]\n",
      "Train Epoch: 86 [0/50000 (0%)]\tLoss: 0.019051, Accuracy: 99.61\n",
      "Train Epoch: 86 [1280/50000 (3%)]\tLoss: 0.061095, Accuracy: 96.88\n",
      "Train Epoch: 86 [2560/50000 (6%)]\tLoss: 0.054868, Accuracy: 98.05\n",
      "Train Epoch: 86 [3840/50000 (9%)]\tLoss: 0.077138, Accuracy: 97.27\n",
      "Train Epoch: 86 [5120/50000 (11%)]\tLoss: 0.035546, Accuracy: 98.44\n",
      "Train Epoch: 86 [6400/50000 (14%)]\tLoss: 0.017020, Accuracy: 99.22\n",
      "Train Epoch: 86 [7680/50000 (17%)]\tLoss: 0.046952, Accuracy: 98.83\n",
      "Train Epoch: 86 [8960/50000 (20%)]\tLoss: 0.026789, Accuracy: 98.83\n",
      "Train Epoch: 86 [10240/50000 (23%)]\tLoss: 0.015666, Accuracy: 99.61\n",
      "Train Epoch: 86 [11520/50000 (26%)]\tLoss: 0.064455, Accuracy: 98.44\n",
      "Train Epoch: 86 [12800/50000 (28%)]\tLoss: 0.031347, Accuracy: 98.83\n",
      "Train Epoch: 86 [14080/50000 (31%)]\tLoss: 0.046091, Accuracy: 98.44\n",
      "Train Epoch: 86 [15360/50000 (34%)]\tLoss: 0.028840, Accuracy: 98.83\n",
      "Train Epoch: 86 [16640/50000 (37%)]\tLoss: 0.036773, Accuracy: 98.05\n",
      "Train Epoch: 86 [17920/50000 (40%)]\tLoss: 0.041710, Accuracy: 98.44\n",
      "Train Epoch: 86 [19200/50000 (43%)]\tLoss: 0.038469, Accuracy: 98.44\n",
      "Train Epoch: 86 [20480/50000 (45%)]\tLoss: 0.046743, Accuracy: 98.44\n",
      "Train Epoch: 86 [21760/50000 (48%)]\tLoss: 0.089272, Accuracy: 97.27\n",
      "Train Epoch: 86 [23040/50000 (51%)]\tLoss: 0.018777, Accuracy: 99.61\n",
      "Train Epoch: 86 [24320/50000 (54%)]\tLoss: 0.034644, Accuracy: 98.05\n",
      "Train Epoch: 86 [25600/50000 (57%)]\tLoss: 0.038302, Accuracy: 98.05\n",
      "Train Epoch: 86 [26880/50000 (60%)]\tLoss: 0.062575, Accuracy: 98.05\n",
      "Train Epoch: 86 [28160/50000 (62%)]\tLoss: 0.062790, Accuracy: 96.88\n",
      "Train Epoch: 86 [29440/50000 (65%)]\tLoss: 0.044280, Accuracy: 98.44\n",
      "Train Epoch: 86 [30720/50000 (68%)]\tLoss: 0.029359, Accuracy: 98.83\n",
      "Train Epoch: 86 [32000/50000 (71%)]\tLoss: 0.028338, Accuracy: 98.44\n",
      "Train Epoch: 86 [33280/50000 (74%)]\tLoss: 0.028791, Accuracy: 98.83\n",
      "Train Epoch: 86 [34560/50000 (77%)]\tLoss: 0.047488, Accuracy: 97.27\n",
      "Train Epoch: 86 [35840/50000 (80%)]\tLoss: 0.031004, Accuracy: 99.22\n",
      "Train Epoch: 86 [37120/50000 (82%)]\tLoss: 0.055925, Accuracy: 97.66\n",
      "Train Epoch: 86 [38400/50000 (85%)]\tLoss: 0.088717, Accuracy: 96.09\n",
      "Train Epoch: 86 [39680/50000 (88%)]\tLoss: 0.039254, Accuracy: 98.05\n",
      "Train Epoch: 86 [40960/50000 (91%)]\tLoss: 0.040771, Accuracy: 98.05\n",
      "Train Epoch: 86 [42240/50000 (94%)]\tLoss: 0.022764, Accuracy: 99.22\n",
      "Train Epoch: 86 [43520/50000 (97%)]\tLoss: 0.047182, Accuracy: 98.44\n",
      "Train Epoch: 86 [35000/50000 (99%)]\tLoss: 0.067499, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5018, Accuracy: 4468/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35890555381775 s]\n",
      "Train Epoch: 87 [0/50000 (0%)]\tLoss: 0.047660, Accuracy: 98.44\n",
      "Train Epoch: 87 [1280/50000 (3%)]\tLoss: 0.021124, Accuracy: 98.83\n",
      "Train Epoch: 87 [2560/50000 (6%)]\tLoss: 0.035442, Accuracy: 98.44\n",
      "Train Epoch: 87 [3840/50000 (9%)]\tLoss: 0.032034, Accuracy: 99.22\n",
      "Train Epoch: 87 [5120/50000 (11%)]\tLoss: 0.027915, Accuracy: 98.05\n",
      "Train Epoch: 87 [6400/50000 (14%)]\tLoss: 0.039459, Accuracy: 98.05\n",
      "Train Epoch: 87 [7680/50000 (17%)]\tLoss: 0.053735, Accuracy: 98.05\n",
      "Train Epoch: 87 [8960/50000 (20%)]\tLoss: 0.033307, Accuracy: 99.22\n",
      "Train Epoch: 87 [10240/50000 (23%)]\tLoss: 0.030596, Accuracy: 98.44\n",
      "Train Epoch: 87 [11520/50000 (26%)]\tLoss: 0.053059, Accuracy: 97.66\n",
      "Train Epoch: 87 [12800/50000 (28%)]\tLoss: 0.034019, Accuracy: 98.05\n",
      "Train Epoch: 87 [14080/50000 (31%)]\tLoss: 0.039972, Accuracy: 98.83\n",
      "Train Epoch: 87 [15360/50000 (34%)]\tLoss: 0.027222, Accuracy: 98.83\n",
      "Train Epoch: 87 [16640/50000 (37%)]\tLoss: 0.045805, Accuracy: 98.44\n",
      "Train Epoch: 87 [17920/50000 (40%)]\tLoss: 0.028470, Accuracy: 99.61\n",
      "Train Epoch: 87 [19200/50000 (43%)]\tLoss: 0.049984, Accuracy: 98.83\n",
      "Train Epoch: 87 [20480/50000 (45%)]\tLoss: 0.047511, Accuracy: 98.05\n",
      "Train Epoch: 87 [21760/50000 (48%)]\tLoss: 0.019817, Accuracy: 99.22\n",
      "Train Epoch: 87 [23040/50000 (51%)]\tLoss: 0.034073, Accuracy: 98.83\n",
      "Train Epoch: 87 [24320/50000 (54%)]\tLoss: 0.036356, Accuracy: 98.44\n",
      "Train Epoch: 87 [25600/50000 (57%)]\tLoss: 0.032517, Accuracy: 99.22\n",
      "Train Epoch: 87 [26880/50000 (60%)]\tLoss: 0.041647, Accuracy: 98.44\n",
      "Train Epoch: 87 [28160/50000 (62%)]\tLoss: 0.026275, Accuracy: 98.05\n",
      "Train Epoch: 87 [29440/50000 (65%)]\tLoss: 0.069229, Accuracy: 96.88\n",
      "Train Epoch: 87 [30720/50000 (68%)]\tLoss: 0.055567, Accuracy: 97.27\n",
      "Train Epoch: 87 [32000/50000 (71%)]\tLoss: 0.038432, Accuracy: 98.44\n",
      "Train Epoch: 87 [33280/50000 (74%)]\tLoss: 0.032571, Accuracy: 98.44\n",
      "Train Epoch: 87 [34560/50000 (77%)]\tLoss: 0.017229, Accuracy: 99.61\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 87 [35840/50000 (80%)]\tLoss: 0.042402, Accuracy: 99.22\n",
      "Train Epoch: 87 [37120/50000 (82%)]\tLoss: 0.058016, Accuracy: 97.66\n",
      "Train Epoch: 87 [38400/50000 (85%)]\tLoss: 0.047482, Accuracy: 98.83\n",
      "Train Epoch: 87 [39680/50000 (88%)]\tLoss: 0.036073, Accuracy: 98.83\n",
      "Train Epoch: 87 [40960/50000 (91%)]\tLoss: 0.032041, Accuracy: 98.44\n",
      "Train Epoch: 87 [42240/50000 (94%)]\tLoss: 0.048129, Accuracy: 98.44\n",
      "Train Epoch: 87 [43520/50000 (97%)]\tLoss: 0.052721, Accuracy: 97.27\n",
      "Train Epoch: 87 [35000/50000 (99%)]\tLoss: 0.056939, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.4996, Accuracy: 4476/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.39188051223755 s]\n",
      "Train Epoch: 88 [0/50000 (0%)]\tLoss: 0.033222, Accuracy: 98.83\n",
      "Train Epoch: 88 [1280/50000 (3%)]\tLoss: 0.018729, Accuracy: 99.22\n",
      "Train Epoch: 88 [2560/50000 (6%)]\tLoss: 0.015509, Accuracy: 99.61\n",
      "Train Epoch: 88 [3840/50000 (9%)]\tLoss: 0.066577, Accuracy: 98.44\n",
      "Train Epoch: 88 [5120/50000 (11%)]\tLoss: 0.024048, Accuracy: 99.61\n",
      "Train Epoch: 88 [6400/50000 (14%)]\tLoss: 0.032698, Accuracy: 98.83\n",
      "Train Epoch: 88 [7680/50000 (17%)]\tLoss: 0.030830, Accuracy: 99.22\n",
      "Train Epoch: 88 [8960/50000 (20%)]\tLoss: 0.019662, Accuracy: 99.61\n",
      "Train Epoch: 88 [10240/50000 (23%)]\tLoss: 0.041101, Accuracy: 98.05\n",
      "Train Epoch: 88 [11520/50000 (26%)]\tLoss: 0.035018, Accuracy: 98.83\n",
      "Train Epoch: 88 [12800/50000 (28%)]\tLoss: 0.038324, Accuracy: 99.61\n",
      "Train Epoch: 88 [14080/50000 (31%)]\tLoss: 0.027914, Accuracy: 98.83\n",
      "Train Epoch: 88 [15360/50000 (34%)]\tLoss: 0.048899, Accuracy: 99.22\n",
      "Train Epoch: 88 [16640/50000 (37%)]\tLoss: 0.063111, Accuracy: 98.83\n",
      "Train Epoch: 88 [17920/50000 (40%)]\tLoss: 0.026801, Accuracy: 98.44\n",
      "Train Epoch: 88 [19200/50000 (43%)]\tLoss: 0.034072, Accuracy: 98.83\n",
      "Train Epoch: 88 [20480/50000 (45%)]\tLoss: 0.028273, Accuracy: 98.44\n",
      "Train Epoch: 88 [21760/50000 (48%)]\tLoss: 0.039381, Accuracy: 98.44\n",
      "Train Epoch: 88 [23040/50000 (51%)]\tLoss: 0.039194, Accuracy: 98.44\n",
      "Train Epoch: 88 [24320/50000 (54%)]\tLoss: 0.037257, Accuracy: 98.83\n",
      "Train Epoch: 88 [25600/50000 (57%)]\tLoss: 0.040009, Accuracy: 99.22\n",
      "Train Epoch: 88 [26880/50000 (60%)]\tLoss: 0.038118, Accuracy: 98.83\n",
      "Train Epoch: 88 [28160/50000 (62%)]\tLoss: 0.032247, Accuracy: 99.22\n",
      "Train Epoch: 88 [29440/50000 (65%)]\tLoss: 0.049062, Accuracy: 98.05\n",
      "Train Epoch: 88 [30720/50000 (68%)]\tLoss: 0.106017, Accuracy: 96.88\n",
      "Train Epoch: 88 [32000/50000 (71%)]\tLoss: 0.018520, Accuracy: 99.22\n",
      "Train Epoch: 88 [33280/50000 (74%)]\tLoss: 0.059230, Accuracy: 98.44\n",
      "Train Epoch: 88 [34560/50000 (77%)]\tLoss: 0.047113, Accuracy: 98.44\n",
      "Train Epoch: 88 [35840/50000 (80%)]\tLoss: 0.051298, Accuracy: 98.05\n",
      "Train Epoch: 88 [37120/50000 (82%)]\tLoss: 0.029693, Accuracy: 98.44\n",
      "Train Epoch: 88 [38400/50000 (85%)]\tLoss: 0.032458, Accuracy: 99.22\n",
      "Train Epoch: 88 [39680/50000 (88%)]\tLoss: 0.083079, Accuracy: 96.88\n",
      "Train Epoch: 88 [40960/50000 (91%)]\tLoss: 0.018459, Accuracy: 99.61\n",
      "Train Epoch: 88 [42240/50000 (94%)]\tLoss: 0.024603, Accuracy: 98.83\n",
      "Train Epoch: 88 [43520/50000 (97%)]\tLoss: 0.043780, Accuracy: 98.83\n",
      "Train Epoch: 88 [35000/50000 (99%)]\tLoss: 0.023522, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5026, Accuracy: 4464/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.386235237121582 s]\n",
      "Train Epoch: 89 [0/50000 (0%)]\tLoss: 0.012988, Accuracy: 100.00\n",
      "Train Epoch: 89 [1280/50000 (3%)]\tLoss: 0.065334, Accuracy: 98.05\n",
      "Train Epoch: 89 [2560/50000 (6%)]\tLoss: 0.032477, Accuracy: 98.83\n",
      "Train Epoch: 89 [3840/50000 (9%)]\tLoss: 0.051211, Accuracy: 98.44\n",
      "Train Epoch: 89 [5120/50000 (11%)]\tLoss: 0.035097, Accuracy: 98.05\n",
      "Train Epoch: 89 [6400/50000 (14%)]\tLoss: 0.052558, Accuracy: 97.66\n",
      "Train Epoch: 89 [7680/50000 (17%)]\tLoss: 0.039355, Accuracy: 98.83\n",
      "Train Epoch: 89 [8960/50000 (20%)]\tLoss: 0.050007, Accuracy: 99.22\n",
      "Train Epoch: 89 [10240/50000 (23%)]\tLoss: 0.045204, Accuracy: 98.05\n",
      "Train Epoch: 89 [11520/50000 (26%)]\tLoss: 0.040709, Accuracy: 98.05\n",
      "Train Epoch: 89 [12800/50000 (28%)]\tLoss: 0.055850, Accuracy: 98.05\n",
      "Train Epoch: 89 [14080/50000 (31%)]\tLoss: 0.026776, Accuracy: 99.22\n",
      "Train Epoch: 89 [15360/50000 (34%)]\tLoss: 0.030711, Accuracy: 98.44\n",
      "Train Epoch: 89 [16640/50000 (37%)]\tLoss: 0.026293, Accuracy: 99.22\n",
      "Train Epoch: 89 [17920/50000 (40%)]\tLoss: 0.046712, Accuracy: 98.44\n",
      "Train Epoch: 89 [19200/50000 (43%)]\tLoss: 0.047697, Accuracy: 97.27\n",
      "Train Epoch: 89 [20480/50000 (45%)]\tLoss: 0.060101, Accuracy: 97.66\n",
      "Train Epoch: 89 [21760/50000 (48%)]\tLoss: 0.061984, Accuracy: 98.05\n",
      "Train Epoch: 89 [23040/50000 (51%)]\tLoss: 0.020199, Accuracy: 99.22\n",
      "Train Epoch: 89 [24320/50000 (54%)]\tLoss: 0.026321, Accuracy: 99.22\n",
      "Train Epoch: 89 [25600/50000 (57%)]\tLoss: 0.029798, Accuracy: 98.83\n",
      "Train Epoch: 89 [26880/50000 (60%)]\tLoss: 0.029987, Accuracy: 99.22\n",
      "Train Epoch: 89 [28160/50000 (62%)]\tLoss: 0.036804, Accuracy: 98.83\n",
      "Train Epoch: 89 [29440/50000 (65%)]\tLoss: 0.042049, Accuracy: 98.44\n",
      "Train Epoch: 89 [30720/50000 (68%)]\tLoss: 0.047288, Accuracy: 98.44\n",
      "Train Epoch: 89 [32000/50000 (71%)]\tLoss: 0.039576, Accuracy: 98.83\n",
      "Train Epoch: 89 [33280/50000 (74%)]\tLoss: 0.072183, Accuracy: 97.66\n",
      "Train Epoch: 89 [34560/50000 (77%)]\tLoss: 0.024019, Accuracy: 98.83\n",
      "Train Epoch: 89 [35840/50000 (80%)]\tLoss: 0.025822, Accuracy: 99.22\n",
      "Train Epoch: 89 [37120/50000 (82%)]\tLoss: 0.058108, Accuracy: 98.05\n",
      "Train Epoch: 89 [38400/50000 (85%)]\tLoss: 0.030329, Accuracy: 98.83\n",
      "Train Epoch: 89 [39680/50000 (88%)]\tLoss: 0.024163, Accuracy: 99.22\n",
      "Train Epoch: 89 [40960/50000 (91%)]\tLoss: 0.067859, Accuracy: 97.66\n",
      "Train Epoch: 89 [42240/50000 (94%)]\tLoss: 0.012724, Accuracy: 99.22\n",
      "Train Epoch: 89 [43520/50000 (97%)]\tLoss: 0.055989, Accuracy: 98.44\n",
      "Train Epoch: 89 [35000/50000 (99%)]\tLoss: 0.042127, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5120, Accuracy: 4471/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.369599103927612 s]\n",
      "Train Epoch: 90 [0/50000 (0%)]\tLoss: 0.054968, Accuracy: 98.05\n",
      "Train Epoch: 90 [1280/50000 (3%)]\tLoss: 0.032593, Accuracy: 98.83\n",
      "Train Epoch: 90 [2560/50000 (6%)]\tLoss: 0.017423, Accuracy: 100.00\n",
      "Train Epoch: 90 [3840/50000 (9%)]\tLoss: 0.064519, Accuracy: 96.88\n",
      "Train Epoch: 90 [5120/50000 (11%)]\tLoss: 0.044494, Accuracy: 98.44\n",
      "Train Epoch: 90 [6400/50000 (14%)]\tLoss: 0.043332, Accuracy: 98.05\n",
      "Train Epoch: 90 [7680/50000 (17%)]\tLoss: 0.030488, Accuracy: 98.83\n",
      "Train Epoch: 90 [8960/50000 (20%)]\tLoss: 0.011133, Accuracy: 99.22\n",
      "Train Epoch: 90 [10240/50000 (23%)]\tLoss: 0.042162, Accuracy: 98.05\n",
      "Train Epoch: 90 [11520/50000 (26%)]\tLoss: 0.010384, Accuracy: 99.61\n",
      "Train Epoch: 90 [12800/50000 (28%)]\tLoss: 0.016804, Accuracy: 99.61\n",
      "Train Epoch: 90 [14080/50000 (31%)]\tLoss: 0.023641, Accuracy: 99.22\n",
      "Train Epoch: 90 [15360/50000 (34%)]\tLoss: 0.052554, Accuracy: 97.66\n",
      "Train Epoch: 90 [16640/50000 (37%)]\tLoss: 0.024148, Accuracy: 99.61\n",
      "Train Epoch: 90 [17920/50000 (40%)]\tLoss: 0.035371, Accuracy: 98.05\n",
      "Train Epoch: 90 [19200/50000 (43%)]\tLoss: 0.039011, Accuracy: 98.44\n",
      "Train Epoch: 90 [20480/50000 (45%)]\tLoss: 0.032611, Accuracy: 99.22\n",
      "Train Epoch: 90 [21760/50000 (48%)]\tLoss: 0.034548, Accuracy: 98.44\n",
      "Train Epoch: 90 [23040/50000 (51%)]\tLoss: 0.044454, Accuracy: 97.66\n",
      "Train Epoch: 90 [24320/50000 (54%)]\tLoss: 0.019974, Accuracy: 99.61\n",
      "Train Epoch: 90 [25600/50000 (57%)]\tLoss: 0.033365, Accuracy: 98.83\n",
      "Train Epoch: 90 [26880/50000 (60%)]\tLoss: 0.053892, Accuracy: 97.66\n",
      "Train Epoch: 90 [28160/50000 (62%)]\tLoss: 0.024290, Accuracy: 98.83\n",
      "Train Epoch: 90 [29440/50000 (65%)]\tLoss: 0.077501, Accuracy: 97.27\n",
      "Train Epoch: 90 [30720/50000 (68%)]\tLoss: 0.044469, Accuracy: 98.05\n",
      "Train Epoch: 90 [32000/50000 (71%)]\tLoss: 0.051692, Accuracy: 98.83\n",
      "Train Epoch: 90 [33280/50000 (74%)]\tLoss: 0.043061, Accuracy: 98.83\n",
      "Train Epoch: 90 [34560/50000 (77%)]\tLoss: 0.037354, Accuracy: 98.05\n",
      "Train Epoch: 90 [35840/50000 (80%)]\tLoss: 0.051041, Accuracy: 97.27\n",
      "Train Epoch: 90 [37120/50000 (82%)]\tLoss: 0.032801, Accuracy: 98.83\n",
      "Train Epoch: 90 [38400/50000 (85%)]\tLoss: 0.009435, Accuracy: 100.00\n",
      "Train Epoch: 90 [39680/50000 (88%)]\tLoss: 0.034616, Accuracy: 99.22\n",
      "Train Epoch: 90 [40960/50000 (91%)]\tLoss: 0.020090, Accuracy: 99.22\n",
      "Train Epoch: 90 [42240/50000 (94%)]\tLoss: 0.065441, Accuracy: 98.44\n",
      "Train Epoch: 90 [43520/50000 (97%)]\tLoss: 0.029096, Accuracy: 99.22\n",
      "Train Epoch: 90 [35000/50000 (99%)]\tLoss: 0.049373, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5003, Accuracy: 4491/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.377736806869507 s]\n",
      "Train Epoch: 91 [0/50000 (0%)]\tLoss: 0.025352, Accuracy: 98.83\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 91 [1280/50000 (3%)]\tLoss: 0.040041, Accuracy: 98.44\n",
      "Train Epoch: 91 [2560/50000 (6%)]\tLoss: 0.038470, Accuracy: 98.83\n",
      "Train Epoch: 91 [3840/50000 (9%)]\tLoss: 0.034934, Accuracy: 98.05\n",
      "Train Epoch: 91 [5120/50000 (11%)]\tLoss: 0.035669, Accuracy: 98.83\n",
      "Train Epoch: 91 [6400/50000 (14%)]\tLoss: 0.030033, Accuracy: 99.22\n",
      "Train Epoch: 91 [7680/50000 (17%)]\tLoss: 0.028149, Accuracy: 99.22\n",
      "Train Epoch: 91 [8960/50000 (20%)]\tLoss: 0.045952, Accuracy: 98.44\n",
      "Train Epoch: 91 [10240/50000 (23%)]\tLoss: 0.019907, Accuracy: 99.22\n",
      "Train Epoch: 91 [11520/50000 (26%)]\tLoss: 0.041565, Accuracy: 98.44\n",
      "Train Epoch: 91 [12800/50000 (28%)]\tLoss: 0.010181, Accuracy: 99.61\n",
      "Train Epoch: 91 [14080/50000 (31%)]\tLoss: 0.022582, Accuracy: 98.83\n",
      "Train Epoch: 91 [15360/50000 (34%)]\tLoss: 0.058643, Accuracy: 98.44\n",
      "Train Epoch: 91 [16640/50000 (37%)]\tLoss: 0.028828, Accuracy: 99.22\n",
      "Train Epoch: 91 [17920/50000 (40%)]\tLoss: 0.026512, Accuracy: 98.44\n",
      "Train Epoch: 91 [19200/50000 (43%)]\tLoss: 0.041602, Accuracy: 98.05\n",
      "Train Epoch: 91 [20480/50000 (45%)]\tLoss: 0.022656, Accuracy: 99.22\n",
      "Train Epoch: 91 [21760/50000 (48%)]\tLoss: 0.043764, Accuracy: 98.83\n",
      "Train Epoch: 91 [23040/50000 (51%)]\tLoss: 0.043665, Accuracy: 97.66\n",
      "Train Epoch: 91 [24320/50000 (54%)]\tLoss: 0.029637, Accuracy: 98.83\n",
      "Train Epoch: 91 [25600/50000 (57%)]\tLoss: 0.013977, Accuracy: 99.61\n",
      "Train Epoch: 91 [26880/50000 (60%)]\tLoss: 0.028375, Accuracy: 99.22\n",
      "Train Epoch: 91 [28160/50000 (62%)]\tLoss: 0.050554, Accuracy: 97.66\n",
      "Train Epoch: 91 [29440/50000 (65%)]\tLoss: 0.123009, Accuracy: 96.48\n",
      "Train Epoch: 91 [30720/50000 (68%)]\tLoss: 0.011725, Accuracy: 99.61\n",
      "Train Epoch: 91 [32000/50000 (71%)]\tLoss: 0.034832, Accuracy: 99.61\n",
      "Train Epoch: 91 [33280/50000 (74%)]\tLoss: 0.034246, Accuracy: 99.22\n",
      "Train Epoch: 91 [34560/50000 (77%)]\tLoss: 0.066672, Accuracy: 97.27\n",
      "Train Epoch: 91 [35840/50000 (80%)]\tLoss: 0.062220, Accuracy: 97.66\n",
      "Train Epoch: 91 [37120/50000 (82%)]\tLoss: 0.029880, Accuracy: 98.44\n",
      "Train Epoch: 91 [38400/50000 (85%)]\tLoss: 0.013454, Accuracy: 99.61\n",
      "Train Epoch: 91 [39680/50000 (88%)]\tLoss: 0.029622, Accuracy: 99.22\n",
      "Train Epoch: 91 [40960/50000 (91%)]\tLoss: 0.065655, Accuracy: 97.66\n",
      "Train Epoch: 91 [42240/50000 (94%)]\tLoss: 0.056057, Accuracy: 98.05\n",
      "Train Epoch: 91 [43520/50000 (97%)]\tLoss: 0.040872, Accuracy: 98.05\n",
      "Train Epoch: 91 [35000/50000 (99%)]\tLoss: 0.007554, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5032, Accuracy: 4486/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.388152360916138 s]\n",
      "Train Epoch: 92 [0/50000 (0%)]\tLoss: 0.033169, Accuracy: 98.05\n",
      "Train Epoch: 92 [1280/50000 (3%)]\tLoss: 0.024010, Accuracy: 98.83\n",
      "Train Epoch: 92 [2560/50000 (6%)]\tLoss: 0.039432, Accuracy: 98.05\n",
      "Train Epoch: 92 [3840/50000 (9%)]\tLoss: 0.042241, Accuracy: 98.05\n",
      "Train Epoch: 92 [5120/50000 (11%)]\tLoss: 0.006488, Accuracy: 100.00\n",
      "Train Epoch: 92 [6400/50000 (14%)]\tLoss: 0.041180, Accuracy: 98.05\n",
      "Train Epoch: 92 [7680/50000 (17%)]\tLoss: 0.031525, Accuracy: 99.22\n",
      "Train Epoch: 92 [8960/50000 (20%)]\tLoss: 0.023531, Accuracy: 98.83\n",
      "Train Epoch: 92 [10240/50000 (23%)]\tLoss: 0.027431, Accuracy: 98.83\n",
      "Train Epoch: 92 [11520/50000 (26%)]\tLoss: 0.049826, Accuracy: 97.66\n",
      "Train Epoch: 92 [12800/50000 (28%)]\tLoss: 0.015631, Accuracy: 99.22\n",
      "Train Epoch: 92 [14080/50000 (31%)]\tLoss: 0.046671, Accuracy: 98.44\n",
      "Train Epoch: 92 [15360/50000 (34%)]\tLoss: 0.040006, Accuracy: 98.44\n",
      "Train Epoch: 92 [16640/50000 (37%)]\tLoss: 0.027285, Accuracy: 98.83\n",
      "Train Epoch: 92 [17920/50000 (40%)]\tLoss: 0.047971, Accuracy: 97.27\n",
      "Train Epoch: 92 [19200/50000 (43%)]\tLoss: 0.026316, Accuracy: 99.22\n",
      "Train Epoch: 92 [20480/50000 (45%)]\tLoss: 0.032600, Accuracy: 98.83\n",
      "Train Epoch: 92 [21760/50000 (48%)]\tLoss: 0.040023, Accuracy: 97.66\n",
      "Train Epoch: 92 [23040/50000 (51%)]\tLoss: 0.024074, Accuracy: 99.61\n",
      "Train Epoch: 92 [24320/50000 (54%)]\tLoss: 0.066978, Accuracy: 97.27\n",
      "Train Epoch: 92 [25600/50000 (57%)]\tLoss: 0.050718, Accuracy: 97.66\n",
      "Train Epoch: 92 [26880/50000 (60%)]\tLoss: 0.014255, Accuracy: 99.61\n",
      "Train Epoch: 92 [28160/50000 (62%)]\tLoss: 0.048716, Accuracy: 98.83\n",
      "Train Epoch: 92 [29440/50000 (65%)]\tLoss: 0.029173, Accuracy: 98.44\n",
      "Train Epoch: 92 [30720/50000 (68%)]\tLoss: 0.023166, Accuracy: 99.22\n",
      "Train Epoch: 92 [32000/50000 (71%)]\tLoss: 0.070171, Accuracy: 96.88\n",
      "Train Epoch: 92 [33280/50000 (74%)]\tLoss: 0.021160, Accuracy: 98.83\n",
      "Train Epoch: 92 [34560/50000 (77%)]\tLoss: 0.035732, Accuracy: 98.44\n",
      "Train Epoch: 92 [35840/50000 (80%)]\tLoss: 0.029702, Accuracy: 98.83\n",
      "Train Epoch: 92 [37120/50000 (82%)]\tLoss: 0.025436, Accuracy: 98.44\n",
      "Train Epoch: 92 [38400/50000 (85%)]\tLoss: 0.020296, Accuracy: 99.22\n",
      "Train Epoch: 92 [39680/50000 (88%)]\tLoss: 0.059649, Accuracy: 98.44\n",
      "Train Epoch: 92 [40960/50000 (91%)]\tLoss: 0.025672, Accuracy: 98.83\n",
      "Train Epoch: 92 [42240/50000 (94%)]\tLoss: 0.041726, Accuracy: 98.44\n",
      "Train Epoch: 92 [43520/50000 (97%)]\tLoss: 0.037070, Accuracy: 98.83\n",
      "Train Epoch: 92 [35000/50000 (99%)]\tLoss: 0.044570, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5095, Accuracy: 4465/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.378072261810303 s]\n",
      "Train Epoch: 93 [0/50000 (0%)]\tLoss: 0.015435, Accuracy: 99.22\n",
      "Train Epoch: 93 [1280/50000 (3%)]\tLoss: 0.045804, Accuracy: 98.83\n",
      "Train Epoch: 93 [2560/50000 (6%)]\tLoss: 0.032280, Accuracy: 99.22\n",
      "Train Epoch: 93 [3840/50000 (9%)]\tLoss: 0.045443, Accuracy: 98.44\n",
      "Train Epoch: 93 [5120/50000 (11%)]\tLoss: 0.035991, Accuracy: 98.83\n",
      "Train Epoch: 93 [6400/50000 (14%)]\tLoss: 0.046259, Accuracy: 98.05\n",
      "Train Epoch: 93 [7680/50000 (17%)]\tLoss: 0.034120, Accuracy: 99.22\n",
      "Train Epoch: 93 [8960/50000 (20%)]\tLoss: 0.035323, Accuracy: 98.44\n",
      "Train Epoch: 93 [10240/50000 (23%)]\tLoss: 0.013489, Accuracy: 100.00\n",
      "Train Epoch: 93 [11520/50000 (26%)]\tLoss: 0.034651, Accuracy: 98.44\n",
      "Train Epoch: 93 [12800/50000 (28%)]\tLoss: 0.019832, Accuracy: 99.22\n",
      "Train Epoch: 93 [14080/50000 (31%)]\tLoss: 0.032534, Accuracy: 99.22\n",
      "Train Epoch: 93 [15360/50000 (34%)]\tLoss: 0.043133, Accuracy: 98.05\n",
      "Train Epoch: 93 [16640/50000 (37%)]\tLoss: 0.039296, Accuracy: 98.44\n",
      "Train Epoch: 93 [17920/50000 (40%)]\tLoss: 0.055757, Accuracy: 96.88\n",
      "Train Epoch: 93 [19200/50000 (43%)]\tLoss: 0.048471, Accuracy: 98.83\n",
      "Train Epoch: 93 [20480/50000 (45%)]\tLoss: 0.016490, Accuracy: 99.22\n",
      "Train Epoch: 93 [21760/50000 (48%)]\tLoss: 0.019121, Accuracy: 99.61\n",
      "Train Epoch: 93 [23040/50000 (51%)]\tLoss: 0.031295, Accuracy: 99.22\n",
      "Train Epoch: 93 [24320/50000 (54%)]\tLoss: 0.041511, Accuracy: 98.44\n",
      "Train Epoch: 93 [25600/50000 (57%)]\tLoss: 0.035036, Accuracy: 98.83\n",
      "Train Epoch: 93 [26880/50000 (60%)]\tLoss: 0.028204, Accuracy: 99.22\n",
      "Train Epoch: 93 [28160/50000 (62%)]\tLoss: 0.031429, Accuracy: 98.83\n",
      "Train Epoch: 93 [29440/50000 (65%)]\tLoss: 0.010516, Accuracy: 99.61\n",
      "Train Epoch: 93 [30720/50000 (68%)]\tLoss: 0.035514, Accuracy: 98.44\n",
      "Train Epoch: 93 [32000/50000 (71%)]\tLoss: 0.034631, Accuracy: 98.44\n",
      "Train Epoch: 93 [33280/50000 (74%)]\tLoss: 0.021572, Accuracy: 99.61\n",
      "Train Epoch: 93 [34560/50000 (77%)]\tLoss: 0.059097, Accuracy: 98.05\n",
      "Train Epoch: 93 [35840/50000 (80%)]\tLoss: 0.014067, Accuracy: 100.00\n",
      "Train Epoch: 93 [37120/50000 (82%)]\tLoss: 0.056966, Accuracy: 97.27\n",
      "Train Epoch: 93 [38400/50000 (85%)]\tLoss: 0.019217, Accuracy: 99.22\n",
      "Train Epoch: 93 [39680/50000 (88%)]\tLoss: 0.053446, Accuracy: 98.44\n",
      "Train Epoch: 93 [40960/50000 (91%)]\tLoss: 0.028848, Accuracy: 99.22\n",
      "Train Epoch: 93 [42240/50000 (94%)]\tLoss: 0.066612, Accuracy: 97.66\n",
      "Train Epoch: 93 [43520/50000 (97%)]\tLoss: 0.051366, Accuracy: 98.05\n",
      "Train Epoch: 93 [35000/50000 (99%)]\tLoss: 0.023441, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5219, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.37520146369934 s]\n",
      "Train Epoch: 94 [0/50000 (0%)]\tLoss: 0.010574, Accuracy: 100.00\n",
      "Train Epoch: 94 [1280/50000 (3%)]\tLoss: 0.011413, Accuracy: 100.00\n",
      "Train Epoch: 94 [2560/50000 (6%)]\tLoss: 0.011531, Accuracy: 99.61\n",
      "Train Epoch: 94 [3840/50000 (9%)]\tLoss: 0.044603, Accuracy: 98.05\n",
      "Train Epoch: 94 [5120/50000 (11%)]\tLoss: 0.034241, Accuracy: 98.44\n",
      "Train Epoch: 94 [6400/50000 (14%)]\tLoss: 0.044123, Accuracy: 98.83\n",
      "Train Epoch: 94 [7680/50000 (17%)]\tLoss: 0.032340, Accuracy: 98.44\n",
      "Train Epoch: 94 [8960/50000 (20%)]\tLoss: 0.023415, Accuracy: 99.61\n",
      "Train Epoch: 94 [10240/50000 (23%)]\tLoss: 0.035189, Accuracy: 98.05\n",
      "Train Epoch: 94 [11520/50000 (26%)]\tLoss: 0.031413, Accuracy: 98.44\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 94 [12800/50000 (28%)]\tLoss: 0.047251, Accuracy: 98.83\n",
      "Train Epoch: 94 [14080/50000 (31%)]\tLoss: 0.049370, Accuracy: 97.66\n",
      "Train Epoch: 94 [15360/50000 (34%)]\tLoss: 0.027795, Accuracy: 98.83\n",
      "Train Epoch: 94 [16640/50000 (37%)]\tLoss: 0.050057, Accuracy: 97.27\n",
      "Train Epoch: 94 [17920/50000 (40%)]\tLoss: 0.032676, Accuracy: 98.44\n",
      "Train Epoch: 94 [19200/50000 (43%)]\tLoss: 0.013922, Accuracy: 99.61\n",
      "Train Epoch: 94 [20480/50000 (45%)]\tLoss: 0.065695, Accuracy: 98.05\n",
      "Train Epoch: 94 [21760/50000 (48%)]\tLoss: 0.044540, Accuracy: 98.05\n",
      "Train Epoch: 94 [23040/50000 (51%)]\tLoss: 0.040612, Accuracy: 98.05\n",
      "Train Epoch: 94 [24320/50000 (54%)]\tLoss: 0.045931, Accuracy: 98.83\n",
      "Train Epoch: 94 [25600/50000 (57%)]\tLoss: 0.032305, Accuracy: 99.22\n",
      "Train Epoch: 94 [26880/50000 (60%)]\tLoss: 0.051031, Accuracy: 98.44\n",
      "Train Epoch: 94 [28160/50000 (62%)]\tLoss: 0.013335, Accuracy: 99.22\n",
      "Train Epoch: 94 [29440/50000 (65%)]\tLoss: 0.027577, Accuracy: 99.22\n",
      "Train Epoch: 94 [30720/50000 (68%)]\tLoss: 0.050495, Accuracy: 98.05\n",
      "Train Epoch: 94 [32000/50000 (71%)]\tLoss: 0.033888, Accuracy: 98.44\n",
      "Train Epoch: 94 [33280/50000 (74%)]\tLoss: 0.054930, Accuracy: 98.05\n",
      "Train Epoch: 94 [34560/50000 (77%)]\tLoss: 0.043195, Accuracy: 98.83\n",
      "Train Epoch: 94 [35840/50000 (80%)]\tLoss: 0.041598, Accuracy: 98.44\n",
      "Train Epoch: 94 [37120/50000 (82%)]\tLoss: 0.016240, Accuracy: 99.61\n",
      "Train Epoch: 94 [38400/50000 (85%)]\tLoss: 0.024403, Accuracy: 98.83\n",
      "Train Epoch: 94 [39680/50000 (88%)]\tLoss: 0.034461, Accuracy: 97.66\n",
      "Train Epoch: 94 [40960/50000 (91%)]\tLoss: 0.057981, Accuracy: 98.44\n",
      "Train Epoch: 94 [42240/50000 (94%)]\tLoss: 0.029136, Accuracy: 99.22\n",
      "Train Epoch: 94 [43520/50000 (97%)]\tLoss: 0.034928, Accuracy: 99.22\n",
      "Train Epoch: 94 [35000/50000 (99%)]\tLoss: 0.036625, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5148, Accuracy: 4487/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.380910634994507 s]\n",
      "Train Epoch: 95 [0/50000 (0%)]\tLoss: 0.022520, Accuracy: 99.22\n",
      "Train Epoch: 95 [1280/50000 (3%)]\tLoss: 0.013341, Accuracy: 99.61\n",
      "Train Epoch: 95 [2560/50000 (6%)]\tLoss: 0.025034, Accuracy: 99.22\n",
      "Train Epoch: 95 [3840/50000 (9%)]\tLoss: 0.057614, Accuracy: 98.05\n",
      "Train Epoch: 95 [5120/50000 (11%)]\tLoss: 0.012648, Accuracy: 99.61\n",
      "Train Epoch: 95 [6400/50000 (14%)]\tLoss: 0.057195, Accuracy: 98.44\n",
      "Train Epoch: 95 [7680/50000 (17%)]\tLoss: 0.035121, Accuracy: 98.05\n",
      "Train Epoch: 95 [8960/50000 (20%)]\tLoss: 0.042921, Accuracy: 98.44\n",
      "Train Epoch: 95 [10240/50000 (23%)]\tLoss: 0.040350, Accuracy: 98.83\n",
      "Train Epoch: 95 [11520/50000 (26%)]\tLoss: 0.044457, Accuracy: 98.83\n",
      "Train Epoch: 95 [12800/50000 (28%)]\tLoss: 0.038185, Accuracy: 98.83\n",
      "Train Epoch: 95 [14080/50000 (31%)]\tLoss: 0.019152, Accuracy: 99.61\n",
      "Train Epoch: 95 [15360/50000 (34%)]\tLoss: 0.021775, Accuracy: 98.83\n",
      "Train Epoch: 95 [16640/50000 (37%)]\tLoss: 0.048108, Accuracy: 97.66\n",
      "Train Epoch: 95 [17920/50000 (40%)]\tLoss: 0.014826, Accuracy: 99.61\n",
      "Train Epoch: 95 [19200/50000 (43%)]\tLoss: 0.027391, Accuracy: 99.22\n",
      "Train Epoch: 95 [20480/50000 (45%)]\tLoss: 0.040093, Accuracy: 98.44\n",
      "Train Epoch: 95 [21760/50000 (48%)]\tLoss: 0.041680, Accuracy: 97.27\n",
      "Train Epoch: 95 [23040/50000 (51%)]\tLoss: 0.035028, Accuracy: 98.83\n",
      "Train Epoch: 95 [24320/50000 (54%)]\tLoss: 0.062319, Accuracy: 98.05\n",
      "Train Epoch: 95 [25600/50000 (57%)]\tLoss: 0.020813, Accuracy: 99.61\n",
      "Train Epoch: 95 [26880/50000 (60%)]\tLoss: 0.047149, Accuracy: 98.05\n",
      "Train Epoch: 95 [28160/50000 (62%)]\tLoss: 0.035349, Accuracy: 98.05\n",
      "Train Epoch: 95 [29440/50000 (65%)]\tLoss: 0.021583, Accuracy: 99.22\n",
      "Train Epoch: 95 [30720/50000 (68%)]\tLoss: 0.034240, Accuracy: 98.05\n",
      "Train Epoch: 95 [32000/50000 (71%)]\tLoss: 0.027251, Accuracy: 99.61\n",
      "Train Epoch: 95 [33280/50000 (74%)]\tLoss: 0.067003, Accuracy: 97.66\n",
      "Train Epoch: 95 [34560/50000 (77%)]\tLoss: 0.050653, Accuracy: 98.05\n",
      "Train Epoch: 95 [35840/50000 (80%)]\tLoss: 0.057018, Accuracy: 97.27\n",
      "Train Epoch: 95 [37120/50000 (82%)]\tLoss: 0.034085, Accuracy: 98.44\n",
      "Train Epoch: 95 [38400/50000 (85%)]\tLoss: 0.038911, Accuracy: 98.83\n",
      "Train Epoch: 95 [39680/50000 (88%)]\tLoss: 0.010809, Accuracy: 100.00\n",
      "Train Epoch: 95 [40960/50000 (91%)]\tLoss: 0.031808, Accuracy: 98.83\n",
      "Train Epoch: 95 [42240/50000 (94%)]\tLoss: 0.029868, Accuracy: 98.05\n",
      "Train Epoch: 95 [43520/50000 (97%)]\tLoss: 0.012943, Accuracy: 99.61\n",
      "Train Epoch: 95 [35000/50000 (99%)]\tLoss: 0.064135, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5251, Accuracy: 4477/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.379374027252197 s]\n",
      "Train Epoch: 96 [0/50000 (0%)]\tLoss: 0.051310, Accuracy: 98.44\n",
      "Train Epoch: 96 [1280/50000 (3%)]\tLoss: 0.018030, Accuracy: 99.61\n",
      "Train Epoch: 96 [2560/50000 (6%)]\tLoss: 0.050397, Accuracy: 98.05\n",
      "Train Epoch: 96 [3840/50000 (9%)]\tLoss: 0.029812, Accuracy: 98.83\n",
      "Train Epoch: 96 [5120/50000 (11%)]\tLoss: 0.014388, Accuracy: 99.61\n",
      "Train Epoch: 96 [6400/50000 (14%)]\tLoss: 0.060025, Accuracy: 96.88\n",
      "Train Epoch: 96 [7680/50000 (17%)]\tLoss: 0.025766, Accuracy: 99.61\n",
      "Train Epoch: 96 [8960/50000 (20%)]\tLoss: 0.049026, Accuracy: 97.27\n",
      "Train Epoch: 96 [10240/50000 (23%)]\tLoss: 0.027616, Accuracy: 98.44\n",
      "Train Epoch: 96 [11520/50000 (26%)]\tLoss: 0.031147, Accuracy: 99.22\n",
      "Train Epoch: 96 [12800/50000 (28%)]\tLoss: 0.043364, Accuracy: 98.05\n",
      "Train Epoch: 96 [14080/50000 (31%)]\tLoss: 0.047924, Accuracy: 98.05\n",
      "Train Epoch: 96 [15360/50000 (34%)]\tLoss: 0.028298, Accuracy: 99.61\n",
      "Train Epoch: 96 [16640/50000 (37%)]\tLoss: 0.021017, Accuracy: 99.22\n",
      "Train Epoch: 96 [17920/50000 (40%)]\tLoss: 0.046623, Accuracy: 98.44\n",
      "Train Epoch: 96 [19200/50000 (43%)]\tLoss: 0.031095, Accuracy: 98.83\n",
      "Train Epoch: 96 [20480/50000 (45%)]\tLoss: 0.043455, Accuracy: 98.44\n",
      "Train Epoch: 96 [21760/50000 (48%)]\tLoss: 0.030786, Accuracy: 98.83\n",
      "Train Epoch: 96 [23040/50000 (51%)]\tLoss: 0.033137, Accuracy: 98.83\n",
      "Train Epoch: 96 [24320/50000 (54%)]\tLoss: 0.064477, Accuracy: 97.66\n",
      "Train Epoch: 96 [25600/50000 (57%)]\tLoss: 0.062052, Accuracy: 96.88\n",
      "Train Epoch: 96 [26880/50000 (60%)]\tLoss: 0.044520, Accuracy: 98.44\n",
      "Train Epoch: 96 [28160/50000 (62%)]\tLoss: 0.021553, Accuracy: 99.22\n",
      "Train Epoch: 96 [29440/50000 (65%)]\tLoss: 0.030013, Accuracy: 98.83\n",
      "Train Epoch: 96 [30720/50000 (68%)]\tLoss: 0.030512, Accuracy: 99.61\n",
      "Train Epoch: 96 [32000/50000 (71%)]\tLoss: 0.041940, Accuracy: 98.44\n",
      "Train Epoch: 96 [33280/50000 (74%)]\tLoss: 0.036077, Accuracy: 98.44\n",
      "Train Epoch: 96 [34560/50000 (77%)]\tLoss: 0.030888, Accuracy: 98.83\n",
      "Train Epoch: 96 [35840/50000 (80%)]\tLoss: 0.030668, Accuracy: 98.83\n",
      "Train Epoch: 96 [37120/50000 (82%)]\tLoss: 0.029487, Accuracy: 99.22\n",
      "Train Epoch: 96 [38400/50000 (85%)]\tLoss: 0.033125, Accuracy: 98.05\n",
      "Train Epoch: 96 [39680/50000 (88%)]\tLoss: 0.021188, Accuracy: 99.61\n",
      "Train Epoch: 96 [40960/50000 (91%)]\tLoss: 0.086785, Accuracy: 97.27\n",
      "Train Epoch: 96 [42240/50000 (94%)]\tLoss: 0.049577, Accuracy: 97.66\n",
      "Train Epoch: 96 [43520/50000 (97%)]\tLoss: 0.037847, Accuracy: 98.44\n",
      "Train Epoch: 96 [35000/50000 (99%)]\tLoss: 0.026607, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5068, Accuracy: 4497/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.375059366226196 s]\n",
      "Train Epoch: 97 [0/50000 (0%)]\tLoss: 0.038040, Accuracy: 98.83\n",
      "Train Epoch: 97 [1280/50000 (3%)]\tLoss: 0.040310, Accuracy: 98.83\n",
      "Train Epoch: 97 [2560/50000 (6%)]\tLoss: 0.029161, Accuracy: 99.22\n",
      "Train Epoch: 97 [3840/50000 (9%)]\tLoss: 0.011195, Accuracy: 100.00\n",
      "Train Epoch: 97 [5120/50000 (11%)]\tLoss: 0.048552, Accuracy: 98.05\n",
      "Train Epoch: 97 [6400/50000 (14%)]\tLoss: 0.031137, Accuracy: 99.22\n",
      "Train Epoch: 97 [7680/50000 (17%)]\tLoss: 0.039383, Accuracy: 98.83\n",
      "Train Epoch: 97 [8960/50000 (20%)]\tLoss: 0.017883, Accuracy: 99.61\n",
      "Train Epoch: 97 [10240/50000 (23%)]\tLoss: 0.031241, Accuracy: 99.61\n",
      "Train Epoch: 97 [11520/50000 (26%)]\tLoss: 0.069220, Accuracy: 97.66\n",
      "Train Epoch: 97 [12800/50000 (28%)]\tLoss: 0.025896, Accuracy: 99.22\n",
      "Train Epoch: 97 [14080/50000 (31%)]\tLoss: 0.026376, Accuracy: 98.83\n",
      "Train Epoch: 97 [15360/50000 (34%)]\tLoss: 0.021182, Accuracy: 99.61\n",
      "Train Epoch: 97 [16640/50000 (37%)]\tLoss: 0.018424, Accuracy: 99.22\n",
      "Train Epoch: 97 [17920/50000 (40%)]\tLoss: 0.064982, Accuracy: 97.66\n",
      "Train Epoch: 97 [19200/50000 (43%)]\tLoss: 0.030322, Accuracy: 98.44\n",
      "Train Epoch: 97 [20480/50000 (45%)]\tLoss: 0.062447, Accuracy: 97.66\n",
      "Train Epoch: 97 [21760/50000 (48%)]\tLoss: 0.064477, Accuracy: 97.66\n",
      "Train Epoch: 97 [23040/50000 (51%)]\tLoss: 0.029924, Accuracy: 98.44\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 97 [24320/50000 (54%)]\tLoss: 0.032302, Accuracy: 98.44\n",
      "Train Epoch: 97 [25600/50000 (57%)]\tLoss: 0.031270, Accuracy: 98.44\n",
      "Train Epoch: 97 [26880/50000 (60%)]\tLoss: 0.017567, Accuracy: 98.83\n",
      "Train Epoch: 97 [28160/50000 (62%)]\tLoss: 0.021165, Accuracy: 99.61\n",
      "Train Epoch: 97 [29440/50000 (65%)]\tLoss: 0.071820, Accuracy: 98.44\n",
      "Train Epoch: 97 [30720/50000 (68%)]\tLoss: 0.028204, Accuracy: 98.83\n",
      "Train Epoch: 97 [32000/50000 (71%)]\tLoss: 0.053658, Accuracy: 97.27\n",
      "Train Epoch: 97 [33280/50000 (74%)]\tLoss: 0.023653, Accuracy: 98.44\n",
      "Train Epoch: 97 [34560/50000 (77%)]\tLoss: 0.037608, Accuracy: 99.22\n",
      "Train Epoch: 97 [35840/50000 (80%)]\tLoss: 0.033750, Accuracy: 99.22\n",
      "Train Epoch: 97 [37120/50000 (82%)]\tLoss: 0.039355, Accuracy: 98.44\n",
      "Train Epoch: 97 [38400/50000 (85%)]\tLoss: 0.038942, Accuracy: 98.44\n",
      "Train Epoch: 97 [39680/50000 (88%)]\tLoss: 0.023085, Accuracy: 98.83\n",
      "Train Epoch: 97 [40960/50000 (91%)]\tLoss: 0.036412, Accuracy: 98.44\n",
      "Train Epoch: 97 [42240/50000 (94%)]\tLoss: 0.032775, Accuracy: 98.44\n",
      "Train Epoch: 97 [43520/50000 (97%)]\tLoss: 0.046612, Accuracy: 98.05\n",
      "Train Epoch: 97 [35000/50000 (99%)]\tLoss: 0.013519, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5189, Accuracy: 4488/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.359352588653564 s]\n",
      "Train Epoch: 98 [0/50000 (0%)]\tLoss: 0.009788, Accuracy: 99.61\n",
      "Train Epoch: 98 [1280/50000 (3%)]\tLoss: 0.025825, Accuracy: 98.44\n",
      "Train Epoch: 98 [2560/50000 (6%)]\tLoss: 0.063833, Accuracy: 98.05\n",
      "Train Epoch: 98 [3840/50000 (9%)]\tLoss: 0.050776, Accuracy: 97.66\n",
      "Train Epoch: 98 [5120/50000 (11%)]\tLoss: 0.043039, Accuracy: 98.05\n",
      "Train Epoch: 98 [6400/50000 (14%)]\tLoss: 0.017805, Accuracy: 99.22\n",
      "Train Epoch: 98 [7680/50000 (17%)]\tLoss: 0.023485, Accuracy: 99.22\n",
      "Train Epoch: 98 [8960/50000 (20%)]\tLoss: 0.024253, Accuracy: 99.22\n",
      "Train Epoch: 98 [10240/50000 (23%)]\tLoss: 0.080229, Accuracy: 98.05\n",
      "Train Epoch: 98 [11520/50000 (26%)]\tLoss: 0.015631, Accuracy: 99.61\n",
      "Train Epoch: 98 [12800/50000 (28%)]\tLoss: 0.023578, Accuracy: 99.61\n",
      "Train Epoch: 98 [14080/50000 (31%)]\tLoss: 0.042176, Accuracy: 98.44\n",
      "Train Epoch: 98 [15360/50000 (34%)]\tLoss: 0.028632, Accuracy: 99.22\n",
      "Train Epoch: 98 [16640/50000 (37%)]\tLoss: 0.073254, Accuracy: 96.88\n",
      "Train Epoch: 98 [17920/50000 (40%)]\tLoss: 0.016171, Accuracy: 99.22\n",
      "Train Epoch: 98 [19200/50000 (43%)]\tLoss: 0.025493, Accuracy: 98.44\n",
      "Train Epoch: 98 [20480/50000 (45%)]\tLoss: 0.065337, Accuracy: 99.22\n",
      "Train Epoch: 98 [21760/50000 (48%)]\tLoss: 0.059311, Accuracy: 98.05\n",
      "Train Epoch: 98 [23040/50000 (51%)]\tLoss: 0.032078, Accuracy: 98.05\n",
      "Train Epoch: 98 [24320/50000 (54%)]\tLoss: 0.036140, Accuracy: 98.83\n",
      "Train Epoch: 98 [25600/50000 (57%)]\tLoss: 0.022724, Accuracy: 99.22\n",
      "Train Epoch: 98 [26880/50000 (60%)]\tLoss: 0.031461, Accuracy: 98.44\n",
      "Train Epoch: 98 [28160/50000 (62%)]\tLoss: 0.036244, Accuracy: 98.83\n",
      "Train Epoch: 98 [29440/50000 (65%)]\tLoss: 0.032641, Accuracy: 99.22\n",
      "Train Epoch: 98 [30720/50000 (68%)]\tLoss: 0.026757, Accuracy: 98.44\n",
      "Train Epoch: 98 [32000/50000 (71%)]\tLoss: 0.048811, Accuracy: 98.44\n",
      "Train Epoch: 98 [33280/50000 (74%)]\tLoss: 0.053909, Accuracy: 98.05\n",
      "Train Epoch: 98 [34560/50000 (77%)]\tLoss: 0.059111, Accuracy: 97.66\n",
      "Train Epoch: 98 [35840/50000 (80%)]\tLoss: 0.024422, Accuracy: 98.83\n",
      "Train Epoch: 98 [37120/50000 (82%)]\tLoss: 0.019239, Accuracy: 99.22\n",
      "Train Epoch: 98 [38400/50000 (85%)]\tLoss: 0.014369, Accuracy: 99.61\n",
      "Train Epoch: 98 [39680/50000 (88%)]\tLoss: 0.014941, Accuracy: 99.61\n",
      "Train Epoch: 98 [40960/50000 (91%)]\tLoss: 0.027773, Accuracy: 98.83\n",
      "Train Epoch: 98 [42240/50000 (94%)]\tLoss: 0.030624, Accuracy: 98.44\n",
      "Train Epoch: 98 [43520/50000 (97%)]\tLoss: 0.051506, Accuracy: 97.66\n",
      "Train Epoch: 98 [35000/50000 (99%)]\tLoss: 0.017136, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5256, Accuracy: 4470/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.30189561843872 s]\n",
      "Train Epoch: 99 [0/50000 (0%)]\tLoss: 0.034535, Accuracy: 98.44\n",
      "Train Epoch: 99 [1280/50000 (3%)]\tLoss: 0.022579, Accuracy: 99.22\n",
      "Train Epoch: 99 [2560/50000 (6%)]\tLoss: 0.045232, Accuracy: 98.05\n",
      "Train Epoch: 99 [3840/50000 (9%)]\tLoss: 0.034089, Accuracy: 99.22\n",
      "Train Epoch: 99 [5120/50000 (11%)]\tLoss: 0.034407, Accuracy: 98.83\n",
      "Train Epoch: 99 [6400/50000 (14%)]\tLoss: 0.029591, Accuracy: 98.83\n",
      "Train Epoch: 99 [7680/50000 (17%)]\tLoss: 0.039391, Accuracy: 98.05\n",
      "Train Epoch: 99 [8960/50000 (20%)]\tLoss: 0.020138, Accuracy: 99.22\n",
      "Train Epoch: 99 [10240/50000 (23%)]\tLoss: 0.035769, Accuracy: 99.22\n",
      "Train Epoch: 99 [11520/50000 (26%)]\tLoss: 0.032658, Accuracy: 98.44\n",
      "Train Epoch: 99 [12800/50000 (28%)]\tLoss: 0.063733, Accuracy: 97.27\n",
      "Train Epoch: 99 [14080/50000 (31%)]\tLoss: 0.064670, Accuracy: 98.44\n",
      "Train Epoch: 99 [15360/50000 (34%)]\tLoss: 0.061048, Accuracy: 98.44\n",
      "Train Epoch: 99 [16640/50000 (37%)]\tLoss: 0.051628, Accuracy: 97.66\n",
      "Train Epoch: 99 [17920/50000 (40%)]\tLoss: 0.023283, Accuracy: 99.22\n",
      "Train Epoch: 99 [19200/50000 (43%)]\tLoss: 0.035190, Accuracy: 98.83\n",
      "Train Epoch: 99 [20480/50000 (45%)]\tLoss: 0.038109, Accuracy: 98.05\n",
      "Train Epoch: 99 [21760/50000 (48%)]\tLoss: 0.016990, Accuracy: 99.22\n",
      "Train Epoch: 99 [23040/50000 (51%)]\tLoss: 0.037455, Accuracy: 97.66\n",
      "Train Epoch: 99 [24320/50000 (54%)]\tLoss: 0.045830, Accuracy: 98.44\n",
      "Train Epoch: 99 [25600/50000 (57%)]\tLoss: 0.059496, Accuracy: 97.66\n",
      "Train Epoch: 99 [26880/50000 (60%)]\tLoss: 0.040043, Accuracy: 98.05\n",
      "Train Epoch: 99 [28160/50000 (62%)]\tLoss: 0.053061, Accuracy: 98.05\n",
      "Train Epoch: 99 [29440/50000 (65%)]\tLoss: 0.039682, Accuracy: 98.83\n",
      "Train Epoch: 99 [30720/50000 (68%)]\tLoss: 0.035720, Accuracy: 98.83\n",
      "Train Epoch: 99 [32000/50000 (71%)]\tLoss: 0.057027, Accuracy: 98.83\n",
      "Train Epoch: 99 [33280/50000 (74%)]\tLoss: 0.012517, Accuracy: 99.61\n",
      "Train Epoch: 99 [34560/50000 (77%)]\tLoss: 0.067156, Accuracy: 97.66\n",
      "Train Epoch: 99 [35840/50000 (80%)]\tLoss: 0.032627, Accuracy: 98.05\n",
      "Train Epoch: 99 [37120/50000 (82%)]\tLoss: 0.037489, Accuracy: 98.83\n",
      "Train Epoch: 99 [38400/50000 (85%)]\tLoss: 0.050311, Accuracy: 98.44\n",
      "Train Epoch: 99 [39680/50000 (88%)]\tLoss: 0.036600, Accuracy: 98.83\n",
      "Train Epoch: 99 [40960/50000 (91%)]\tLoss: 0.039022, Accuracy: 98.83\n",
      "Train Epoch: 99 [42240/50000 (94%)]\tLoss: 0.065157, Accuracy: 98.05\n",
      "Train Epoch: 99 [43520/50000 (97%)]\tLoss: 0.017334, Accuracy: 99.61\n",
      "Train Epoch: 99 [35000/50000 (99%)]\tLoss: 0.058298, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5352, Accuracy: 4477/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.313406467437744 s]\n",
      "Train Epoch: 100 [0/50000 (0%)]\tLoss: 0.031103, Accuracy: 99.22\n",
      "Train Epoch: 100 [1280/50000 (3%)]\tLoss: 0.044535, Accuracy: 98.44\n",
      "Train Epoch: 100 [2560/50000 (6%)]\tLoss: 0.038783, Accuracy: 98.05\n",
      "Train Epoch: 100 [3840/50000 (9%)]\tLoss: 0.028167, Accuracy: 99.22\n",
      "Train Epoch: 100 [5120/50000 (11%)]\tLoss: 0.014234, Accuracy: 99.61\n",
      "Train Epoch: 100 [6400/50000 (14%)]\tLoss: 0.038710, Accuracy: 98.44\n",
      "Train Epoch: 100 [7680/50000 (17%)]\tLoss: 0.026900, Accuracy: 98.44\n",
      "Train Epoch: 100 [8960/50000 (20%)]\tLoss: 0.043215, Accuracy: 98.83\n",
      "Train Epoch: 100 [10240/50000 (23%)]\tLoss: 0.015607, Accuracy: 99.61\n",
      "Train Epoch: 100 [11520/50000 (26%)]\tLoss: 0.016559, Accuracy: 99.22\n",
      "Train Epoch: 100 [12800/50000 (28%)]\tLoss: 0.008682, Accuracy: 100.00\n",
      "Train Epoch: 100 [14080/50000 (31%)]\tLoss: 0.032279, Accuracy: 99.22\n",
      "Train Epoch: 100 [15360/50000 (34%)]\tLoss: 0.068923, Accuracy: 96.88\n",
      "Train Epoch: 100 [16640/50000 (37%)]\tLoss: 0.032817, Accuracy: 98.83\n",
      "Train Epoch: 100 [17920/50000 (40%)]\tLoss: 0.042812, Accuracy: 98.44\n",
      "Train Epoch: 100 [19200/50000 (43%)]\tLoss: 0.011968, Accuracy: 100.00\n",
      "Train Epoch: 100 [20480/50000 (45%)]\tLoss: 0.047708, Accuracy: 98.44\n",
      "Train Epoch: 100 [21760/50000 (48%)]\tLoss: 0.041416, Accuracy: 98.44\n",
      "Train Epoch: 100 [23040/50000 (51%)]\tLoss: 0.015971, Accuracy: 99.22\n",
      "Train Epoch: 100 [24320/50000 (54%)]\tLoss: 0.020008, Accuracy: 99.22\n",
      "Train Epoch: 100 [25600/50000 (57%)]\tLoss: 0.043987, Accuracy: 98.05\n",
      "Train Epoch: 100 [26880/50000 (60%)]\tLoss: 0.027495, Accuracy: 99.22\n",
      "Train Epoch: 100 [28160/50000 (62%)]\tLoss: 0.013581, Accuracy: 100.00\n",
      "Train Epoch: 100 [29440/50000 (65%)]\tLoss: 0.043313, Accuracy: 98.44\n",
      "Train Epoch: 100 [30720/50000 (68%)]\tLoss: 0.049571, Accuracy: 98.05\n",
      "Train Epoch: 100 [32000/50000 (71%)]\tLoss: 0.014514, Accuracy: 100.00\n",
      "Train Epoch: 100 [33280/50000 (74%)]\tLoss: 0.018400, Accuracy: 99.22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 100 [34560/50000 (77%)]\tLoss: 0.040485, Accuracy: 98.05\n",
      "Train Epoch: 100 [35840/50000 (80%)]\tLoss: 0.039985, Accuracy: 98.44\n",
      "Train Epoch: 100 [37120/50000 (82%)]\tLoss: 0.019404, Accuracy: 99.22\n",
      "Train Epoch: 100 [38400/50000 (85%)]\tLoss: 0.033203, Accuracy: 98.44\n",
      "Train Epoch: 100 [39680/50000 (88%)]\tLoss: 0.038184, Accuracy: 99.22\n",
      "Train Epoch: 100 [40960/50000 (91%)]\tLoss: 0.056188, Accuracy: 98.44\n",
      "Train Epoch: 100 [42240/50000 (94%)]\tLoss: 0.025611, Accuracy: 98.83\n",
      "Train Epoch: 100 [43520/50000 (97%)]\tLoss: 0.034795, Accuracy: 98.05\n",
      "Train Epoch: 100 [35000/50000 (99%)]\tLoss: 0.029796, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5421, Accuracy: 4453/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.31707501411438 s]\n",
      "Train Epoch: 101 [0/50000 (0%)]\tLoss: 0.029346, Accuracy: 99.22\n",
      "Train Epoch: 101 [1280/50000 (3%)]\tLoss: 0.046871, Accuracy: 98.44\n",
      "Train Epoch: 101 [2560/50000 (6%)]\tLoss: 0.030778, Accuracy: 98.05\n",
      "Train Epoch: 101 [3840/50000 (9%)]\tLoss: 0.053204, Accuracy: 98.83\n",
      "Train Epoch: 101 [5120/50000 (11%)]\tLoss: 0.045857, Accuracy: 98.83\n",
      "Train Epoch: 101 [6400/50000 (14%)]\tLoss: 0.011932, Accuracy: 100.00\n",
      "Train Epoch: 101 [7680/50000 (17%)]\tLoss: 0.046562, Accuracy: 98.05\n",
      "Train Epoch: 101 [8960/50000 (20%)]\tLoss: 0.039592, Accuracy: 98.83\n",
      "Train Epoch: 101 [10240/50000 (23%)]\tLoss: 0.033753, Accuracy: 98.83\n",
      "Train Epoch: 101 [11520/50000 (26%)]\tLoss: 0.059114, Accuracy: 98.05\n",
      "Train Epoch: 101 [12800/50000 (28%)]\tLoss: 0.024656, Accuracy: 99.22\n",
      "Train Epoch: 101 [14080/50000 (31%)]\tLoss: 0.011653, Accuracy: 99.61\n",
      "Train Epoch: 101 [15360/50000 (34%)]\tLoss: 0.045796, Accuracy: 97.66\n",
      "Train Epoch: 101 [16640/50000 (37%)]\tLoss: 0.038013, Accuracy: 98.44\n",
      "Train Epoch: 101 [17920/50000 (40%)]\tLoss: 0.019046, Accuracy: 99.22\n",
      "Train Epoch: 101 [19200/50000 (43%)]\tLoss: 0.034698, Accuracy: 98.44\n",
      "Train Epoch: 101 [20480/50000 (45%)]\tLoss: 0.026152, Accuracy: 99.61\n",
      "Train Epoch: 101 [21760/50000 (48%)]\tLoss: 0.009607, Accuracy: 99.61\n",
      "Train Epoch: 101 [23040/50000 (51%)]\tLoss: 0.018751, Accuracy: 99.22\n",
      "Train Epoch: 101 [24320/50000 (54%)]\tLoss: 0.046849, Accuracy: 98.05\n",
      "Train Epoch: 101 [25600/50000 (57%)]\tLoss: 0.035879, Accuracy: 98.44\n",
      "Train Epoch: 101 [26880/50000 (60%)]\tLoss: 0.054935, Accuracy: 98.44\n",
      "Train Epoch: 101 [28160/50000 (62%)]\tLoss: 0.025998, Accuracy: 99.22\n",
      "Train Epoch: 101 [29440/50000 (65%)]\tLoss: 0.038875, Accuracy: 98.44\n",
      "Train Epoch: 101 [30720/50000 (68%)]\tLoss: 0.018678, Accuracy: 99.61\n",
      "Train Epoch: 101 [32000/50000 (71%)]\tLoss: 0.037468, Accuracy: 99.22\n",
      "Train Epoch: 101 [33280/50000 (74%)]\tLoss: 0.040894, Accuracy: 98.83\n",
      "Train Epoch: 101 [34560/50000 (77%)]\tLoss: 0.076209, Accuracy: 98.05\n",
      "Train Epoch: 101 [35840/50000 (80%)]\tLoss: 0.038063, Accuracy: 99.22\n",
      "Train Epoch: 101 [37120/50000 (82%)]\tLoss: 0.031669, Accuracy: 98.83\n",
      "Train Epoch: 101 [38400/50000 (85%)]\tLoss: 0.014487, Accuracy: 99.61\n",
      "Train Epoch: 101 [39680/50000 (88%)]\tLoss: 0.021802, Accuracy: 99.22\n",
      "Train Epoch: 101 [40960/50000 (91%)]\tLoss: 0.028035, Accuracy: 99.22\n",
      "Train Epoch: 101 [42240/50000 (94%)]\tLoss: 0.025287, Accuracy: 98.83\n",
      "Train Epoch: 101 [43520/50000 (97%)]\tLoss: 0.045272, Accuracy: 98.83\n",
      "Train Epoch: 101 [35000/50000 (99%)]\tLoss: 0.023055, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5081, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.325823068618774 s]\n",
      "Train Epoch: 102 [0/50000 (0%)]\tLoss: 0.043980, Accuracy: 98.05\n",
      "Train Epoch: 102 [1280/50000 (3%)]\tLoss: 0.035174, Accuracy: 98.44\n",
      "Train Epoch: 102 [2560/50000 (6%)]\tLoss: 0.058852, Accuracy: 98.05\n",
      "Train Epoch: 102 [3840/50000 (9%)]\tLoss: 0.057905, Accuracy: 98.05\n",
      "Train Epoch: 102 [5120/50000 (11%)]\tLoss: 0.065163, Accuracy: 97.66\n",
      "Train Epoch: 102 [6400/50000 (14%)]\tLoss: 0.020430, Accuracy: 99.61\n",
      "Train Epoch: 102 [7680/50000 (17%)]\tLoss: 0.026992, Accuracy: 98.83\n",
      "Train Epoch: 102 [8960/50000 (20%)]\tLoss: 0.027779, Accuracy: 98.83\n",
      "Train Epoch: 102 [10240/50000 (23%)]\tLoss: 0.083102, Accuracy: 96.88\n",
      "Train Epoch: 102 [11520/50000 (26%)]\tLoss: 0.026646, Accuracy: 98.44\n",
      "Train Epoch: 102 [12800/50000 (28%)]\tLoss: 0.038884, Accuracy: 98.44\n",
      "Train Epoch: 102 [14080/50000 (31%)]\tLoss: 0.025134, Accuracy: 98.83\n",
      "Train Epoch: 102 [15360/50000 (34%)]\tLoss: 0.035566, Accuracy: 98.44\n",
      "Train Epoch: 102 [16640/50000 (37%)]\tLoss: 0.058167, Accuracy: 97.66\n",
      "Train Epoch: 102 [17920/50000 (40%)]\tLoss: 0.042913, Accuracy: 98.83\n",
      "Train Epoch: 102 [19200/50000 (43%)]\tLoss: 0.022880, Accuracy: 98.83\n",
      "Train Epoch: 102 [20480/50000 (45%)]\tLoss: 0.020044, Accuracy: 99.22\n",
      "Train Epoch: 102 [21760/50000 (48%)]\tLoss: 0.013696, Accuracy: 100.00\n",
      "Train Epoch: 102 [23040/50000 (51%)]\tLoss: 0.020467, Accuracy: 99.61\n",
      "Train Epoch: 102 [24320/50000 (54%)]\tLoss: 0.020912, Accuracy: 99.22\n",
      "Train Epoch: 102 [25600/50000 (57%)]\tLoss: 0.067734, Accuracy: 97.27\n",
      "Train Epoch: 102 [26880/50000 (60%)]\tLoss: 0.043945, Accuracy: 98.83\n",
      "Train Epoch: 102 [28160/50000 (62%)]\tLoss: 0.038003, Accuracy: 98.44\n",
      "Train Epoch: 102 [29440/50000 (65%)]\tLoss: 0.015199, Accuracy: 99.61\n",
      "Train Epoch: 102 [30720/50000 (68%)]\tLoss: 0.055836, Accuracy: 97.66\n",
      "Train Epoch: 102 [32000/50000 (71%)]\tLoss: 0.019932, Accuracy: 98.83\n",
      "Train Epoch: 102 [33280/50000 (74%)]\tLoss: 0.030069, Accuracy: 99.61\n",
      "Train Epoch: 102 [34560/50000 (77%)]\tLoss: 0.033541, Accuracy: 98.83\n",
      "Train Epoch: 102 [35840/50000 (80%)]\tLoss: 0.040253, Accuracy: 98.83\n",
      "Train Epoch: 102 [37120/50000 (82%)]\tLoss: 0.048481, Accuracy: 98.05\n",
      "Train Epoch: 102 [38400/50000 (85%)]\tLoss: 0.017997, Accuracy: 99.22\n",
      "Train Epoch: 102 [39680/50000 (88%)]\tLoss: 0.026208, Accuracy: 99.22\n",
      "Train Epoch: 102 [40960/50000 (91%)]\tLoss: 0.045264, Accuracy: 97.66\n",
      "Train Epoch: 102 [42240/50000 (94%)]\tLoss: 0.018785, Accuracy: 99.61\n",
      "Train Epoch: 102 [43520/50000 (97%)]\tLoss: 0.022842, Accuracy: 98.83\n",
      "Train Epoch: 102 [35000/50000 (99%)]\tLoss: 0.029383, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5123, Accuracy: 4492/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.340627908706665 s]\n",
      "Train Epoch: 103 [0/50000 (0%)]\tLoss: 0.024466, Accuracy: 99.22\n",
      "Train Epoch: 103 [1280/50000 (3%)]\tLoss: 0.026320, Accuracy: 99.22\n",
      "Train Epoch: 103 [2560/50000 (6%)]\tLoss: 0.021018, Accuracy: 99.22\n",
      "Train Epoch: 103 [3840/50000 (9%)]\tLoss: 0.019268, Accuracy: 99.61\n",
      "Train Epoch: 103 [5120/50000 (11%)]\tLoss: 0.012775, Accuracy: 99.61\n",
      "Train Epoch: 103 [6400/50000 (14%)]\tLoss: 0.025917, Accuracy: 98.83\n",
      "Train Epoch: 103 [7680/50000 (17%)]\tLoss: 0.042201, Accuracy: 98.44\n",
      "Train Epoch: 103 [8960/50000 (20%)]\tLoss: 0.105334, Accuracy: 96.88\n",
      "Train Epoch: 103 [10240/50000 (23%)]\tLoss: 0.035160, Accuracy: 98.05\n",
      "Train Epoch: 103 [11520/50000 (26%)]\tLoss: 0.009029, Accuracy: 100.00\n",
      "Train Epoch: 103 [12800/50000 (28%)]\tLoss: 0.023671, Accuracy: 99.22\n",
      "Train Epoch: 103 [14080/50000 (31%)]\tLoss: 0.036774, Accuracy: 98.05\n",
      "Train Epoch: 103 [15360/50000 (34%)]\tLoss: 0.032660, Accuracy: 98.83\n",
      "Train Epoch: 103 [16640/50000 (37%)]\tLoss: 0.026329, Accuracy: 99.22\n",
      "Train Epoch: 103 [17920/50000 (40%)]\tLoss: 0.063035, Accuracy: 98.05\n",
      "Train Epoch: 103 [19200/50000 (43%)]\tLoss: 0.027922, Accuracy: 98.83\n",
      "Train Epoch: 103 [20480/50000 (45%)]\tLoss: 0.008750, Accuracy: 100.00\n",
      "Train Epoch: 103 [21760/50000 (48%)]\tLoss: 0.021255, Accuracy: 98.83\n",
      "Train Epoch: 103 [23040/50000 (51%)]\tLoss: 0.052959, Accuracy: 97.66\n",
      "Train Epoch: 103 [24320/50000 (54%)]\tLoss: 0.019920, Accuracy: 99.22\n",
      "Train Epoch: 103 [25600/50000 (57%)]\tLoss: 0.041527, Accuracy: 98.44\n",
      "Train Epoch: 103 [26880/50000 (60%)]\tLoss: 0.024297, Accuracy: 99.22\n",
      "Train Epoch: 103 [28160/50000 (62%)]\tLoss: 0.016279, Accuracy: 99.61\n",
      "Train Epoch: 103 [29440/50000 (65%)]\tLoss: 0.023187, Accuracy: 99.61\n",
      "Train Epoch: 103 [30720/50000 (68%)]\tLoss: 0.029602, Accuracy: 99.22\n",
      "Train Epoch: 103 [32000/50000 (71%)]\tLoss: 0.030691, Accuracy: 98.83\n",
      "Train Epoch: 103 [33280/50000 (74%)]\tLoss: 0.029198, Accuracy: 98.44\n",
      "Train Epoch: 103 [34560/50000 (77%)]\tLoss: 0.017196, Accuracy: 99.61\n",
      "Train Epoch: 103 [35840/50000 (80%)]\tLoss: 0.040324, Accuracy: 98.44\n",
      "Train Epoch: 103 [37120/50000 (82%)]\tLoss: 0.018203, Accuracy: 99.61\n",
      "Train Epoch: 103 [38400/50000 (85%)]\tLoss: 0.036321, Accuracy: 99.22\n",
      "Train Epoch: 103 [39680/50000 (88%)]\tLoss: 0.016824, Accuracy: 99.61\n",
      "Train Epoch: 103 [40960/50000 (91%)]\tLoss: 0.014408, Accuracy: 99.61\n",
      "Train Epoch: 103 [42240/50000 (94%)]\tLoss: 0.020536, Accuracy: 99.22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 103 [43520/50000 (97%)]\tLoss: 0.065355, Accuracy: 98.05\n",
      "Train Epoch: 103 [35000/50000 (99%)]\tLoss: 0.091067, Accuracy: 97.00\n",
      "\n",
      "Validation set: Average loss: 0.5276, Accuracy: 4473/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.336154222488403 s]\n",
      "Train Epoch: 104 [0/50000 (0%)]\tLoss: 0.029035, Accuracy: 98.83\n",
      "Train Epoch: 104 [1280/50000 (3%)]\tLoss: 0.039018, Accuracy: 98.83\n",
      "Train Epoch: 104 [2560/50000 (6%)]\tLoss: 0.025319, Accuracy: 99.61\n",
      "Train Epoch: 104 [3840/50000 (9%)]\tLoss: 0.022744, Accuracy: 98.83\n",
      "Train Epoch: 104 [5120/50000 (11%)]\tLoss: 0.008509, Accuracy: 100.00\n",
      "Train Epoch: 104 [6400/50000 (14%)]\tLoss: 0.046362, Accuracy: 99.22\n",
      "Train Epoch: 104 [7680/50000 (17%)]\tLoss: 0.032212, Accuracy: 98.83\n",
      "Train Epoch: 104 [8960/50000 (20%)]\tLoss: 0.028810, Accuracy: 98.83\n",
      "Train Epoch: 104 [10240/50000 (23%)]\tLoss: 0.028280, Accuracy: 99.22\n",
      "Train Epoch: 104 [11520/50000 (26%)]\tLoss: 0.033164, Accuracy: 99.61\n",
      "Train Epoch: 104 [12800/50000 (28%)]\tLoss: 0.017801, Accuracy: 99.22\n",
      "Train Epoch: 104 [14080/50000 (31%)]\tLoss: 0.045328, Accuracy: 98.83\n",
      "Train Epoch: 104 [15360/50000 (34%)]\tLoss: 0.029560, Accuracy: 98.83\n",
      "Train Epoch: 104 [16640/50000 (37%)]\tLoss: 0.015068, Accuracy: 99.22\n",
      "Train Epoch: 104 [17920/50000 (40%)]\tLoss: 0.023442, Accuracy: 99.22\n",
      "Train Epoch: 104 [19200/50000 (43%)]\tLoss: 0.022470, Accuracy: 98.83\n",
      "Train Epoch: 104 [20480/50000 (45%)]\tLoss: 0.049852, Accuracy: 98.83\n",
      "Train Epoch: 104 [21760/50000 (48%)]\tLoss: 0.041743, Accuracy: 98.44\n",
      "Train Epoch: 104 [23040/50000 (51%)]\tLoss: 0.045295, Accuracy: 98.05\n",
      "Train Epoch: 104 [24320/50000 (54%)]\tLoss: 0.031899, Accuracy: 98.83\n",
      "Train Epoch: 104 [25600/50000 (57%)]\tLoss: 0.023953, Accuracy: 98.83\n",
      "Train Epoch: 104 [26880/50000 (60%)]\tLoss: 0.019412, Accuracy: 99.61\n",
      "Train Epoch: 104 [28160/50000 (62%)]\tLoss: 0.020953, Accuracy: 99.22\n",
      "Train Epoch: 104 [29440/50000 (65%)]\tLoss: 0.018523, Accuracy: 99.22\n",
      "Train Epoch: 104 [30720/50000 (68%)]\tLoss: 0.050183, Accuracy: 98.05\n",
      "Train Epoch: 104 [32000/50000 (71%)]\tLoss: 0.028123, Accuracy: 98.44\n",
      "Train Epoch: 104 [33280/50000 (74%)]\tLoss: 0.025546, Accuracy: 99.22\n",
      "Train Epoch: 104 [34560/50000 (77%)]\tLoss: 0.043181, Accuracy: 98.44\n",
      "Train Epoch: 104 [35840/50000 (80%)]\tLoss: 0.027325, Accuracy: 99.22\n",
      "Train Epoch: 104 [37120/50000 (82%)]\tLoss: 0.018395, Accuracy: 99.61\n",
      "Train Epoch: 104 [38400/50000 (85%)]\tLoss: 0.017939, Accuracy: 99.61\n",
      "Train Epoch: 104 [39680/50000 (88%)]\tLoss: 0.038313, Accuracy: 98.44\n",
      "Train Epoch: 104 [40960/50000 (91%)]\tLoss: 0.024442, Accuracy: 99.22\n",
      "Train Epoch: 104 [42240/50000 (94%)]\tLoss: 0.032956, Accuracy: 98.83\n",
      "Train Epoch: 104 [43520/50000 (97%)]\tLoss: 0.031086, Accuracy: 98.83\n",
      "Train Epoch: 104 [35000/50000 (99%)]\tLoss: 0.080383, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.5314, Accuracy: 4485/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.354983806610107 s]\n",
      "Train Epoch: 105 [0/50000 (0%)]\tLoss: 0.018530, Accuracy: 99.22\n",
      "Train Epoch: 105 [1280/50000 (3%)]\tLoss: 0.015561, Accuracy: 99.61\n",
      "Train Epoch: 105 [2560/50000 (6%)]\tLoss: 0.023664, Accuracy: 98.83\n",
      "Train Epoch: 105 [3840/50000 (9%)]\tLoss: 0.034367, Accuracy: 98.83\n",
      "Train Epoch: 105 [5120/50000 (11%)]\tLoss: 0.028660, Accuracy: 99.22\n",
      "Train Epoch: 105 [6400/50000 (14%)]\tLoss: 0.025964, Accuracy: 98.83\n",
      "Train Epoch: 105 [7680/50000 (17%)]\tLoss: 0.032473, Accuracy: 99.61\n",
      "Train Epoch: 105 [8960/50000 (20%)]\tLoss: 0.028964, Accuracy: 98.44\n",
      "Train Epoch: 105 [10240/50000 (23%)]\tLoss: 0.067418, Accuracy: 98.05\n",
      "Train Epoch: 105 [11520/50000 (26%)]\tLoss: 0.024803, Accuracy: 98.44\n",
      "Train Epoch: 105 [12800/50000 (28%)]\tLoss: 0.036214, Accuracy: 98.44\n",
      "Train Epoch: 105 [14080/50000 (31%)]\tLoss: 0.056333, Accuracy: 98.44\n",
      "Train Epoch: 105 [15360/50000 (34%)]\tLoss: 0.015259, Accuracy: 100.00\n",
      "Train Epoch: 105 [16640/50000 (37%)]\tLoss: 0.040141, Accuracy: 99.22\n",
      "Train Epoch: 105 [17920/50000 (40%)]\tLoss: 0.024873, Accuracy: 98.83\n",
      "Train Epoch: 105 [19200/50000 (43%)]\tLoss: 0.009795, Accuracy: 100.00\n",
      "Train Epoch: 105 [20480/50000 (45%)]\tLoss: 0.034806, Accuracy: 98.83\n",
      "Train Epoch: 105 [21760/50000 (48%)]\tLoss: 0.032417, Accuracy: 98.83\n",
      "Train Epoch: 105 [23040/50000 (51%)]\tLoss: 0.059756, Accuracy: 98.83\n",
      "Train Epoch: 105 [24320/50000 (54%)]\tLoss: 0.008439, Accuracy: 99.61\n",
      "Train Epoch: 105 [25600/50000 (57%)]\tLoss: 0.027519, Accuracy: 98.83\n",
      "Train Epoch: 105 [26880/50000 (60%)]\tLoss: 0.032597, Accuracy: 98.83\n",
      "Train Epoch: 105 [28160/50000 (62%)]\tLoss: 0.027763, Accuracy: 99.22\n",
      "Train Epoch: 105 [29440/50000 (65%)]\tLoss: 0.023074, Accuracy: 99.61\n",
      "Train Epoch: 105 [30720/50000 (68%)]\tLoss: 0.051230, Accuracy: 97.66\n",
      "Train Epoch: 105 [32000/50000 (71%)]\tLoss: 0.038350, Accuracy: 98.44\n",
      "Train Epoch: 105 [33280/50000 (74%)]\tLoss: 0.031037, Accuracy: 98.83\n",
      "Train Epoch: 105 [34560/50000 (77%)]\tLoss: 0.038157, Accuracy: 99.22\n",
      "Train Epoch: 105 [35840/50000 (80%)]\tLoss: 0.029481, Accuracy: 98.44\n",
      "Train Epoch: 105 [37120/50000 (82%)]\tLoss: 0.016091, Accuracy: 99.22\n",
      "Train Epoch: 105 [38400/50000 (85%)]\tLoss: 0.024579, Accuracy: 99.22\n",
      "Train Epoch: 105 [39680/50000 (88%)]\tLoss: 0.043477, Accuracy: 99.22\n",
      "Train Epoch: 105 [40960/50000 (91%)]\tLoss: 0.020077, Accuracy: 99.22\n",
      "Train Epoch: 105 [42240/50000 (94%)]\tLoss: 0.021100, Accuracy: 99.22\n",
      "Train Epoch: 105 [43520/50000 (97%)]\tLoss: 0.041195, Accuracy: 99.61\n",
      "Train Epoch: 105 [35000/50000 (99%)]\tLoss: 0.032061, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5429, Accuracy: 4453/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35729432106018 s]\n",
      "Train Epoch: 106 [0/50000 (0%)]\tLoss: 0.015164, Accuracy: 99.61\n",
      "Train Epoch: 106 [1280/50000 (3%)]\tLoss: 0.035805, Accuracy: 99.22\n",
      "Train Epoch: 106 [2560/50000 (6%)]\tLoss: 0.015392, Accuracy: 99.61\n",
      "Train Epoch: 106 [3840/50000 (9%)]\tLoss: 0.056917, Accuracy: 98.83\n",
      "Train Epoch: 106 [5120/50000 (11%)]\tLoss: 0.037309, Accuracy: 98.44\n",
      "Train Epoch: 106 [6400/50000 (14%)]\tLoss: 0.014474, Accuracy: 100.00\n",
      "Train Epoch: 106 [7680/50000 (17%)]\tLoss: 0.018825, Accuracy: 99.61\n",
      "Train Epoch: 106 [8960/50000 (20%)]\tLoss: 0.009052, Accuracy: 100.00\n",
      "Train Epoch: 106 [10240/50000 (23%)]\tLoss: 0.008338, Accuracy: 100.00\n",
      "Train Epoch: 106 [11520/50000 (26%)]\tLoss: 0.055532, Accuracy: 98.05\n",
      "Train Epoch: 106 [12800/50000 (28%)]\tLoss: 0.029873, Accuracy: 98.83\n",
      "Train Epoch: 106 [14080/50000 (31%)]\tLoss: 0.040922, Accuracy: 98.05\n",
      "Train Epoch: 106 [15360/50000 (34%)]\tLoss: 0.023838, Accuracy: 98.83\n",
      "Train Epoch: 106 [16640/50000 (37%)]\tLoss: 0.020759, Accuracy: 99.22\n",
      "Train Epoch: 106 [17920/50000 (40%)]\tLoss: 0.009559, Accuracy: 100.00\n",
      "Train Epoch: 106 [19200/50000 (43%)]\tLoss: 0.038519, Accuracy: 98.05\n",
      "Train Epoch: 106 [20480/50000 (45%)]\tLoss: 0.031602, Accuracy: 98.83\n",
      "Train Epoch: 106 [21760/50000 (48%)]\tLoss: 0.013198, Accuracy: 99.22\n",
      "Train Epoch: 106 [23040/50000 (51%)]\tLoss: 0.018547, Accuracy: 99.61\n",
      "Train Epoch: 106 [24320/50000 (54%)]\tLoss: 0.037609, Accuracy: 98.83\n",
      "Train Epoch: 106 [25600/50000 (57%)]\tLoss: 0.014982, Accuracy: 99.61\n",
      "Train Epoch: 106 [26880/50000 (60%)]\tLoss: 0.011209, Accuracy: 99.22\n",
      "Train Epoch: 106 [28160/50000 (62%)]\tLoss: 0.032327, Accuracy: 98.44\n",
      "Train Epoch: 106 [29440/50000 (65%)]\tLoss: 0.048238, Accuracy: 97.66\n",
      "Train Epoch: 106 [30720/50000 (68%)]\tLoss: 0.026595, Accuracy: 99.22\n",
      "Train Epoch: 106 [32000/50000 (71%)]\tLoss: 0.056390, Accuracy: 98.05\n",
      "Train Epoch: 106 [33280/50000 (74%)]\tLoss: 0.033343, Accuracy: 98.83\n",
      "Train Epoch: 106 [34560/50000 (77%)]\tLoss: 0.011974, Accuracy: 100.00\n",
      "Train Epoch: 106 [35840/50000 (80%)]\tLoss: 0.032071, Accuracy: 98.44\n",
      "Train Epoch: 106 [37120/50000 (82%)]\tLoss: 0.015082, Accuracy: 99.22\n",
      "Train Epoch: 106 [38400/50000 (85%)]\tLoss: 0.034967, Accuracy: 98.44\n",
      "Train Epoch: 106 [39680/50000 (88%)]\tLoss: 0.023319, Accuracy: 99.22\n",
      "Train Epoch: 106 [40960/50000 (91%)]\tLoss: 0.037636, Accuracy: 98.44\n",
      "Train Epoch: 106 [42240/50000 (94%)]\tLoss: 0.026675, Accuracy: 99.61\n",
      "Train Epoch: 106 [43520/50000 (97%)]\tLoss: 0.017408, Accuracy: 99.61\n",
      "Train Epoch: 106 [35000/50000 (99%)]\tLoss: 0.021061, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5370, Accuracy: 4466/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.312440156936646 s]\n",
      "Train Epoch: 107 [0/50000 (0%)]\tLoss: 0.022740, Accuracy: 98.83\n",
      "Train Epoch: 107 [1280/50000 (3%)]\tLoss: 0.016265, Accuracy: 99.22\n",
      "Train Epoch: 107 [2560/50000 (6%)]\tLoss: 0.063002, Accuracy: 98.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 107 [3840/50000 (9%)]\tLoss: 0.054486, Accuracy: 98.83\n",
      "Train Epoch: 107 [5120/50000 (11%)]\tLoss: 0.006722, Accuracy: 100.00\n",
      "Train Epoch: 107 [6400/50000 (14%)]\tLoss: 0.039151, Accuracy: 99.22\n",
      "Train Epoch: 107 [7680/50000 (17%)]\tLoss: 0.033520, Accuracy: 98.44\n",
      "Train Epoch: 107 [8960/50000 (20%)]\tLoss: 0.028738, Accuracy: 98.44\n",
      "Train Epoch: 107 [10240/50000 (23%)]\tLoss: 0.016170, Accuracy: 99.61\n",
      "Train Epoch: 107 [11520/50000 (26%)]\tLoss: 0.017311, Accuracy: 99.61\n",
      "Train Epoch: 107 [12800/50000 (28%)]\tLoss: 0.010796, Accuracy: 99.61\n",
      "Train Epoch: 107 [14080/50000 (31%)]\tLoss: 0.004461, Accuracy: 100.00\n",
      "Train Epoch: 107 [15360/50000 (34%)]\tLoss: 0.019777, Accuracy: 98.83\n",
      "Train Epoch: 107 [16640/50000 (37%)]\tLoss: 0.026089, Accuracy: 99.22\n",
      "Train Epoch: 107 [17920/50000 (40%)]\tLoss: 0.035456, Accuracy: 98.05\n",
      "Train Epoch: 107 [19200/50000 (43%)]\tLoss: 0.019969, Accuracy: 99.61\n",
      "Train Epoch: 107 [20480/50000 (45%)]\tLoss: 0.014701, Accuracy: 100.00\n",
      "Train Epoch: 107 [21760/50000 (48%)]\tLoss: 0.034705, Accuracy: 99.22\n",
      "Train Epoch: 107 [23040/50000 (51%)]\tLoss: 0.042147, Accuracy: 98.44\n",
      "Train Epoch: 107 [24320/50000 (54%)]\tLoss: 0.048239, Accuracy: 97.27\n",
      "Train Epoch: 107 [25600/50000 (57%)]\tLoss: 0.047383, Accuracy: 98.83\n",
      "Train Epoch: 107 [26880/50000 (60%)]\tLoss: 0.023392, Accuracy: 99.22\n",
      "Train Epoch: 107 [28160/50000 (62%)]\tLoss: 0.023098, Accuracy: 99.22\n",
      "Train Epoch: 107 [29440/50000 (65%)]\tLoss: 0.026280, Accuracy: 98.83\n",
      "Train Epoch: 107 [30720/50000 (68%)]\tLoss: 0.040164, Accuracy: 98.83\n",
      "Train Epoch: 107 [32000/50000 (71%)]\tLoss: 0.052122, Accuracy: 99.22\n",
      "Train Epoch: 107 [33280/50000 (74%)]\tLoss: 0.041788, Accuracy: 98.83\n",
      "Train Epoch: 107 [34560/50000 (77%)]\tLoss: 0.042193, Accuracy: 98.83\n",
      "Train Epoch: 107 [35840/50000 (80%)]\tLoss: 0.041861, Accuracy: 98.44\n",
      "Train Epoch: 107 [37120/50000 (82%)]\tLoss: 0.006653, Accuracy: 100.00\n",
      "Train Epoch: 107 [38400/50000 (85%)]\tLoss: 0.048442, Accuracy: 98.83\n",
      "Train Epoch: 107 [39680/50000 (88%)]\tLoss: 0.051868, Accuracy: 98.83\n",
      "Train Epoch: 107 [40960/50000 (91%)]\tLoss: 0.054489, Accuracy: 97.66\n",
      "Train Epoch: 107 [42240/50000 (94%)]\tLoss: 0.015558, Accuracy: 99.61\n",
      "Train Epoch: 107 [43520/50000 (97%)]\tLoss: 0.035700, Accuracy: 98.44\n",
      "Train Epoch: 107 [35000/50000 (99%)]\tLoss: 0.023251, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5310, Accuracy: 4485/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.357195138931274 s]\n",
      "Train Epoch: 108 [0/50000 (0%)]\tLoss: 0.072757, Accuracy: 97.27\n",
      "Train Epoch: 108 [1280/50000 (3%)]\tLoss: 0.028413, Accuracy: 98.83\n",
      "Train Epoch: 108 [2560/50000 (6%)]\tLoss: 0.036514, Accuracy: 98.83\n",
      "Train Epoch: 108 [3840/50000 (9%)]\tLoss: 0.028540, Accuracy: 98.44\n",
      "Train Epoch: 108 [5120/50000 (11%)]\tLoss: 0.016101, Accuracy: 99.61\n",
      "Train Epoch: 108 [6400/50000 (14%)]\tLoss: 0.054893, Accuracy: 98.44\n",
      "Train Epoch: 108 [7680/50000 (17%)]\tLoss: 0.012000, Accuracy: 99.61\n",
      "Train Epoch: 108 [8960/50000 (20%)]\tLoss: 0.005476, Accuracy: 100.00\n",
      "Train Epoch: 108 [10240/50000 (23%)]\tLoss: 0.036170, Accuracy: 98.44\n",
      "Train Epoch: 108 [11520/50000 (26%)]\tLoss: 0.021175, Accuracy: 99.61\n",
      "Train Epoch: 108 [12800/50000 (28%)]\tLoss: 0.021463, Accuracy: 99.22\n",
      "Train Epoch: 108 [14080/50000 (31%)]\tLoss: 0.025564, Accuracy: 99.22\n",
      "Train Epoch: 108 [15360/50000 (34%)]\tLoss: 0.015746, Accuracy: 99.61\n",
      "Train Epoch: 108 [16640/50000 (37%)]\tLoss: 0.056519, Accuracy: 97.27\n",
      "Train Epoch: 108 [17920/50000 (40%)]\tLoss: 0.028263, Accuracy: 98.83\n",
      "Train Epoch: 108 [19200/50000 (43%)]\tLoss: 0.012181, Accuracy: 99.61\n",
      "Train Epoch: 108 [20480/50000 (45%)]\tLoss: 0.024052, Accuracy: 98.83\n",
      "Train Epoch: 108 [21760/50000 (48%)]\tLoss: 0.021008, Accuracy: 99.22\n",
      "Train Epoch: 108 [23040/50000 (51%)]\tLoss: 0.016700, Accuracy: 99.22\n",
      "Train Epoch: 108 [24320/50000 (54%)]\tLoss: 0.032797, Accuracy: 98.83\n",
      "Train Epoch: 108 [25600/50000 (57%)]\tLoss: 0.042582, Accuracy: 98.05\n",
      "Train Epoch: 108 [26880/50000 (60%)]\tLoss: 0.014849, Accuracy: 99.61\n",
      "Train Epoch: 108 [28160/50000 (62%)]\tLoss: 0.026102, Accuracy: 98.83\n",
      "Train Epoch: 108 [29440/50000 (65%)]\tLoss: 0.009990, Accuracy: 99.61\n",
      "Train Epoch: 108 [30720/50000 (68%)]\tLoss: 0.024001, Accuracy: 99.61\n",
      "Train Epoch: 108 [32000/50000 (71%)]\tLoss: 0.006899, Accuracy: 100.00\n",
      "Train Epoch: 108 [33280/50000 (74%)]\tLoss: 0.014026, Accuracy: 99.61\n",
      "Train Epoch: 108 [34560/50000 (77%)]\tLoss: 0.037905, Accuracy: 99.61\n",
      "Train Epoch: 108 [35840/50000 (80%)]\tLoss: 0.035039, Accuracy: 98.83\n",
      "Train Epoch: 108 [37120/50000 (82%)]\tLoss: 0.018537, Accuracy: 99.61\n",
      "Train Epoch: 108 [38400/50000 (85%)]\tLoss: 0.022919, Accuracy: 98.83\n",
      "Train Epoch: 108 [39680/50000 (88%)]\tLoss: 0.017884, Accuracy: 98.83\n",
      "Train Epoch: 108 [40960/50000 (91%)]\tLoss: 0.075348, Accuracy: 98.05\n",
      "Train Epoch: 108 [42240/50000 (94%)]\tLoss: 0.007776, Accuracy: 99.61\n",
      "Train Epoch: 108 [43520/50000 (97%)]\tLoss: 0.005672, Accuracy: 100.00\n",
      "Train Epoch: 108 [35000/50000 (99%)]\tLoss: 0.030065, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5359, Accuracy: 4474/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.36435341835022 s]\n",
      "Train Epoch: 109 [0/50000 (0%)]\tLoss: 0.007256, Accuracy: 100.00\n",
      "Train Epoch: 109 [1280/50000 (3%)]\tLoss: 0.043248, Accuracy: 98.44\n",
      "Train Epoch: 109 [2560/50000 (6%)]\tLoss: 0.027523, Accuracy: 98.83\n",
      "Train Epoch: 109 [3840/50000 (9%)]\tLoss: 0.017331, Accuracy: 99.61\n",
      "Train Epoch: 109 [5120/50000 (11%)]\tLoss: 0.027068, Accuracy: 99.61\n",
      "Train Epoch: 109 [6400/50000 (14%)]\tLoss: 0.031438, Accuracy: 98.83\n",
      "Train Epoch: 109 [7680/50000 (17%)]\tLoss: 0.009921, Accuracy: 100.00\n",
      "Train Epoch: 109 [8960/50000 (20%)]\tLoss: 0.023624, Accuracy: 98.83\n",
      "Train Epoch: 109 [10240/50000 (23%)]\tLoss: 0.016251, Accuracy: 99.61\n",
      "Train Epoch: 109 [11520/50000 (26%)]\tLoss: 0.038251, Accuracy: 98.83\n",
      "Train Epoch: 109 [12800/50000 (28%)]\tLoss: 0.031370, Accuracy: 98.83\n",
      "Train Epoch: 109 [14080/50000 (31%)]\tLoss: 0.033164, Accuracy: 99.22\n",
      "Train Epoch: 109 [15360/50000 (34%)]\tLoss: 0.029651, Accuracy: 98.83\n",
      "Train Epoch: 109 [16640/50000 (37%)]\tLoss: 0.032719, Accuracy: 98.83\n",
      "Train Epoch: 109 [17920/50000 (40%)]\tLoss: 0.015052, Accuracy: 99.61\n",
      "Train Epoch: 109 [19200/50000 (43%)]\tLoss: 0.019477, Accuracy: 99.61\n",
      "Train Epoch: 109 [20480/50000 (45%)]\tLoss: 0.041074, Accuracy: 98.44\n",
      "Train Epoch: 109 [21760/50000 (48%)]\tLoss: 0.024855, Accuracy: 98.83\n",
      "Train Epoch: 109 [23040/50000 (51%)]\tLoss: 0.019593, Accuracy: 99.22\n",
      "Train Epoch: 109 [24320/50000 (54%)]\tLoss: 0.017952, Accuracy: 98.83\n",
      "Train Epoch: 109 [25600/50000 (57%)]\tLoss: 0.027890, Accuracy: 99.22\n",
      "Train Epoch: 109 [26880/50000 (60%)]\tLoss: 0.016136, Accuracy: 99.22\n",
      "Train Epoch: 109 [28160/50000 (62%)]\tLoss: 0.018940, Accuracy: 99.61\n",
      "Train Epoch: 109 [29440/50000 (65%)]\tLoss: 0.058740, Accuracy: 98.44\n",
      "Train Epoch: 109 [30720/50000 (68%)]\tLoss: 0.020650, Accuracy: 98.44\n",
      "Train Epoch: 109 [32000/50000 (71%)]\tLoss: 0.022475, Accuracy: 99.22\n",
      "Train Epoch: 109 [33280/50000 (74%)]\tLoss: 0.024816, Accuracy: 98.44\n",
      "Train Epoch: 109 [34560/50000 (77%)]\tLoss: 0.016179, Accuracy: 99.61\n",
      "Train Epoch: 109 [35840/50000 (80%)]\tLoss: 0.043304, Accuracy: 99.22\n",
      "Train Epoch: 109 [37120/50000 (82%)]\tLoss: 0.052625, Accuracy: 98.83\n",
      "Train Epoch: 109 [38400/50000 (85%)]\tLoss: 0.026530, Accuracy: 98.83\n",
      "Train Epoch: 109 [39680/50000 (88%)]\tLoss: 0.016319, Accuracy: 99.61\n",
      "Train Epoch: 109 [40960/50000 (91%)]\tLoss: 0.030113, Accuracy: 98.44\n",
      "Train Epoch: 109 [42240/50000 (94%)]\tLoss: 0.068544, Accuracy: 97.27\n",
      "Train Epoch: 109 [43520/50000 (97%)]\tLoss: 0.034277, Accuracy: 98.05\n",
      "Train Epoch: 109 [35000/50000 (99%)]\tLoss: 0.036942, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5385, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.3485369682312 s]\n",
      "Train Epoch: 110 [0/50000 (0%)]\tLoss: 0.042138, Accuracy: 98.44\n",
      "Train Epoch: 110 [1280/50000 (3%)]\tLoss: 0.015197, Accuracy: 99.61\n",
      "Train Epoch: 110 [2560/50000 (6%)]\tLoss: 0.025729, Accuracy: 98.44\n",
      "Train Epoch: 110 [3840/50000 (9%)]\tLoss: 0.028187, Accuracy: 98.44\n",
      "Train Epoch: 110 [5120/50000 (11%)]\tLoss: 0.022908, Accuracy: 98.83\n",
      "Train Epoch: 110 [6400/50000 (14%)]\tLoss: 0.017797, Accuracy: 99.61\n",
      "Train Epoch: 110 [7680/50000 (17%)]\tLoss: 0.024984, Accuracy: 98.83\n",
      "Train Epoch: 110 [8960/50000 (20%)]\tLoss: 0.047084, Accuracy: 98.83\n",
      "Train Epoch: 110 [10240/50000 (23%)]\tLoss: 0.032971, Accuracy: 98.05\n",
      "Train Epoch: 110 [11520/50000 (26%)]\tLoss: 0.029830, Accuracy: 98.83\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 110 [12800/50000 (28%)]\tLoss: 0.025905, Accuracy: 99.22\n",
      "Train Epoch: 110 [14080/50000 (31%)]\tLoss: 0.010135, Accuracy: 100.00\n",
      "Train Epoch: 110 [15360/50000 (34%)]\tLoss: 0.013088, Accuracy: 99.61\n",
      "Train Epoch: 110 [16640/50000 (37%)]\tLoss: 0.033114, Accuracy: 98.83\n",
      "Train Epoch: 110 [17920/50000 (40%)]\tLoss: 0.044334, Accuracy: 98.44\n",
      "Train Epoch: 110 [19200/50000 (43%)]\tLoss: 0.044061, Accuracy: 98.83\n",
      "Train Epoch: 110 [20480/50000 (45%)]\tLoss: 0.038569, Accuracy: 99.22\n",
      "Train Epoch: 110 [21760/50000 (48%)]\tLoss: 0.031096, Accuracy: 98.05\n",
      "Train Epoch: 110 [23040/50000 (51%)]\tLoss: 0.035708, Accuracy: 97.66\n",
      "Train Epoch: 110 [24320/50000 (54%)]\tLoss: 0.033943, Accuracy: 98.83\n",
      "Train Epoch: 110 [25600/50000 (57%)]\tLoss: 0.058007, Accuracy: 98.44\n",
      "Train Epoch: 110 [26880/50000 (60%)]\tLoss: 0.067615, Accuracy: 98.44\n",
      "Train Epoch: 110 [28160/50000 (62%)]\tLoss: 0.044032, Accuracy: 98.83\n",
      "Train Epoch: 110 [29440/50000 (65%)]\tLoss: 0.036539, Accuracy: 98.44\n",
      "Train Epoch: 110 [30720/50000 (68%)]\tLoss: 0.023838, Accuracy: 99.61\n",
      "Train Epoch: 110 [32000/50000 (71%)]\tLoss: 0.015316, Accuracy: 99.22\n",
      "Train Epoch: 110 [33280/50000 (74%)]\tLoss: 0.042296, Accuracy: 98.44\n",
      "Train Epoch: 110 [34560/50000 (77%)]\tLoss: 0.030805, Accuracy: 98.44\n",
      "Train Epoch: 110 [35840/50000 (80%)]\tLoss: 0.048970, Accuracy: 98.44\n",
      "Train Epoch: 110 [37120/50000 (82%)]\tLoss: 0.034081, Accuracy: 98.83\n",
      "Train Epoch: 110 [38400/50000 (85%)]\tLoss: 0.022585, Accuracy: 99.61\n",
      "Train Epoch: 110 [39680/50000 (88%)]\tLoss: 0.013216, Accuracy: 99.61\n",
      "Train Epoch: 110 [40960/50000 (91%)]\tLoss: 0.023107, Accuracy: 99.22\n",
      "Train Epoch: 110 [42240/50000 (94%)]\tLoss: 0.051293, Accuracy: 97.66\n",
      "Train Epoch: 110 [43520/50000 (97%)]\tLoss: 0.019134, Accuracy: 99.61\n",
      "Train Epoch: 110 [35000/50000 (99%)]\tLoss: 0.030660, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5393, Accuracy: 4467/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.358505487442017 s]\n",
      "Train Epoch: 111 [0/50000 (0%)]\tLoss: 0.037899, Accuracy: 98.44\n",
      "Train Epoch: 111 [1280/50000 (3%)]\tLoss: 0.031160, Accuracy: 99.22\n",
      "Train Epoch: 111 [2560/50000 (6%)]\tLoss: 0.028507, Accuracy: 98.83\n",
      "Train Epoch: 111 [3840/50000 (9%)]\tLoss: 0.009354, Accuracy: 99.61\n",
      "Train Epoch: 111 [5120/50000 (11%)]\tLoss: 0.034995, Accuracy: 98.44\n",
      "Train Epoch: 111 [6400/50000 (14%)]\tLoss: 0.030027, Accuracy: 98.83\n",
      "Train Epoch: 111 [7680/50000 (17%)]\tLoss: 0.027872, Accuracy: 98.83\n",
      "Train Epoch: 111 [8960/50000 (20%)]\tLoss: 0.026561, Accuracy: 98.83\n",
      "Train Epoch: 111 [10240/50000 (23%)]\tLoss: 0.075524, Accuracy: 97.27\n",
      "Train Epoch: 111 [11520/50000 (26%)]\tLoss: 0.023471, Accuracy: 99.22\n",
      "Train Epoch: 111 [12800/50000 (28%)]\tLoss: 0.030395, Accuracy: 98.83\n",
      "Train Epoch: 111 [14080/50000 (31%)]\tLoss: 0.038204, Accuracy: 98.44\n",
      "Train Epoch: 111 [15360/50000 (34%)]\tLoss: 0.015065, Accuracy: 99.61\n",
      "Train Epoch: 111 [16640/50000 (37%)]\tLoss: 0.031456, Accuracy: 98.44\n",
      "Train Epoch: 111 [17920/50000 (40%)]\tLoss: 0.013190, Accuracy: 99.61\n",
      "Train Epoch: 111 [19200/50000 (43%)]\tLoss: 0.016708, Accuracy: 99.22\n",
      "Train Epoch: 111 [20480/50000 (45%)]\tLoss: 0.020707, Accuracy: 99.22\n",
      "Train Epoch: 111 [21760/50000 (48%)]\tLoss: 0.039146, Accuracy: 98.05\n",
      "Train Epoch: 111 [23040/50000 (51%)]\tLoss: 0.012544, Accuracy: 99.61\n",
      "Train Epoch: 111 [24320/50000 (54%)]\tLoss: 0.051074, Accuracy: 97.27\n",
      "Train Epoch: 111 [25600/50000 (57%)]\tLoss: 0.041723, Accuracy: 98.83\n",
      "Train Epoch: 111 [26880/50000 (60%)]\tLoss: 0.016717, Accuracy: 98.83\n",
      "Train Epoch: 111 [28160/50000 (62%)]\tLoss: 0.013650, Accuracy: 99.61\n",
      "Train Epoch: 111 [29440/50000 (65%)]\tLoss: 0.018211, Accuracy: 99.22\n",
      "Train Epoch: 111 [30720/50000 (68%)]\tLoss: 0.026092, Accuracy: 98.44\n",
      "Train Epoch: 111 [32000/50000 (71%)]\tLoss: 0.034791, Accuracy: 98.83\n",
      "Train Epoch: 111 [33280/50000 (74%)]\tLoss: 0.034837, Accuracy: 98.05\n",
      "Train Epoch: 111 [34560/50000 (77%)]\tLoss: 0.018068, Accuracy: 99.22\n",
      "Train Epoch: 111 [35840/50000 (80%)]\tLoss: 0.038079, Accuracy: 98.83\n",
      "Train Epoch: 111 [37120/50000 (82%)]\tLoss: 0.036377, Accuracy: 98.05\n",
      "Train Epoch: 111 [38400/50000 (85%)]\tLoss: 0.028658, Accuracy: 98.83\n",
      "Train Epoch: 111 [39680/50000 (88%)]\tLoss: 0.052406, Accuracy: 97.27\n",
      "Train Epoch: 111 [40960/50000 (91%)]\tLoss: 0.026265, Accuracy: 98.83\n",
      "Train Epoch: 111 [42240/50000 (94%)]\tLoss: 0.027105, Accuracy: 99.22\n",
      "Train Epoch: 111 [43520/50000 (97%)]\tLoss: 0.037616, Accuracy: 99.22\n",
      "Train Epoch: 111 [35000/50000 (99%)]\tLoss: 0.038203, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5355, Accuracy: 4488/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.358805179595947 s]\n",
      "Train Epoch: 112 [0/50000 (0%)]\tLoss: 0.030310, Accuracy: 98.05\n",
      "Train Epoch: 112 [1280/50000 (3%)]\tLoss: 0.025656, Accuracy: 98.44\n",
      "Train Epoch: 112 [2560/50000 (6%)]\tLoss: 0.034268, Accuracy: 98.83\n",
      "Train Epoch: 112 [3840/50000 (9%)]\tLoss: 0.014962, Accuracy: 99.22\n",
      "Train Epoch: 112 [5120/50000 (11%)]\tLoss: 0.031965, Accuracy: 99.22\n",
      "Train Epoch: 112 [6400/50000 (14%)]\tLoss: 0.025527, Accuracy: 99.61\n",
      "Train Epoch: 112 [7680/50000 (17%)]\tLoss: 0.012627, Accuracy: 100.00\n",
      "Train Epoch: 112 [8960/50000 (20%)]\tLoss: 0.029293, Accuracy: 98.83\n",
      "Train Epoch: 112 [10240/50000 (23%)]\tLoss: 0.006258, Accuracy: 100.00\n",
      "Train Epoch: 112 [11520/50000 (26%)]\tLoss: 0.029411, Accuracy: 99.22\n",
      "Train Epoch: 112 [12800/50000 (28%)]\tLoss: 0.056254, Accuracy: 98.83\n",
      "Train Epoch: 112 [14080/50000 (31%)]\tLoss: 0.013313, Accuracy: 99.61\n",
      "Train Epoch: 112 [15360/50000 (34%)]\tLoss: 0.008541, Accuracy: 100.00\n",
      "Train Epoch: 112 [16640/50000 (37%)]\tLoss: 0.029268, Accuracy: 98.44\n",
      "Train Epoch: 112 [17920/50000 (40%)]\tLoss: 0.017344, Accuracy: 99.61\n",
      "Train Epoch: 112 [19200/50000 (43%)]\tLoss: 0.035188, Accuracy: 98.83\n",
      "Train Epoch: 112 [20480/50000 (45%)]\tLoss: 0.046121, Accuracy: 98.83\n",
      "Train Epoch: 112 [21760/50000 (48%)]\tLoss: 0.023909, Accuracy: 98.83\n",
      "Train Epoch: 112 [23040/50000 (51%)]\tLoss: 0.007735, Accuracy: 100.00\n",
      "Train Epoch: 112 [24320/50000 (54%)]\tLoss: 0.021434, Accuracy: 99.22\n",
      "Train Epoch: 112 [25600/50000 (57%)]\tLoss: 0.047440, Accuracy: 99.22\n",
      "Train Epoch: 112 [26880/50000 (60%)]\tLoss: 0.013669, Accuracy: 99.61\n",
      "Train Epoch: 112 [28160/50000 (62%)]\tLoss: 0.021652, Accuracy: 99.22\n",
      "Train Epoch: 112 [29440/50000 (65%)]\tLoss: 0.024636, Accuracy: 99.22\n",
      "Train Epoch: 112 [30720/50000 (68%)]\tLoss: 0.020485, Accuracy: 98.83\n",
      "Train Epoch: 112 [32000/50000 (71%)]\tLoss: 0.025088, Accuracy: 98.44\n",
      "Train Epoch: 112 [33280/50000 (74%)]\tLoss: 0.027408, Accuracy: 99.22\n",
      "Train Epoch: 112 [34560/50000 (77%)]\tLoss: 0.032070, Accuracy: 98.83\n",
      "Train Epoch: 112 [35840/50000 (80%)]\tLoss: 0.034167, Accuracy: 98.44\n",
      "Train Epoch: 112 [37120/50000 (82%)]\tLoss: 0.008203, Accuracy: 100.00\n",
      "Train Epoch: 112 [38400/50000 (85%)]\tLoss: 0.025356, Accuracy: 99.22\n",
      "Train Epoch: 112 [39680/50000 (88%)]\tLoss: 0.013909, Accuracy: 99.22\n",
      "Train Epoch: 112 [40960/50000 (91%)]\tLoss: 0.025867, Accuracy: 99.22\n",
      "Train Epoch: 112 [42240/50000 (94%)]\tLoss: 0.013021, Accuracy: 99.61\n",
      "Train Epoch: 112 [43520/50000 (97%)]\tLoss: 0.026665, Accuracy: 99.22\n",
      "Train Epoch: 112 [35000/50000 (99%)]\tLoss: 0.009292, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5446, Accuracy: 4479/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35438060760498 s]\n",
      "Train Epoch: 113 [0/50000 (0%)]\tLoss: 0.018136, Accuracy: 99.22\n",
      "Train Epoch: 113 [1280/50000 (3%)]\tLoss: 0.013052, Accuracy: 99.61\n",
      "Train Epoch: 113 [2560/50000 (6%)]\tLoss: 0.019103, Accuracy: 100.00\n",
      "Train Epoch: 113 [3840/50000 (9%)]\tLoss: 0.045003, Accuracy: 98.83\n",
      "Train Epoch: 113 [5120/50000 (11%)]\tLoss: 0.031968, Accuracy: 98.05\n",
      "Train Epoch: 113 [6400/50000 (14%)]\tLoss: 0.034336, Accuracy: 99.22\n",
      "Train Epoch: 113 [7680/50000 (17%)]\tLoss: 0.041767, Accuracy: 99.22\n",
      "Train Epoch: 113 [8960/50000 (20%)]\tLoss: 0.039617, Accuracy: 98.44\n",
      "Train Epoch: 113 [10240/50000 (23%)]\tLoss: 0.031349, Accuracy: 98.44\n",
      "Train Epoch: 113 [11520/50000 (26%)]\tLoss: 0.024919, Accuracy: 99.61\n",
      "Train Epoch: 113 [12800/50000 (28%)]\tLoss: 0.027256, Accuracy: 99.61\n",
      "Train Epoch: 113 [14080/50000 (31%)]\tLoss: 0.042930, Accuracy: 98.44\n",
      "Train Epoch: 113 [15360/50000 (34%)]\tLoss: 0.007843, Accuracy: 100.00\n",
      "Train Epoch: 113 [16640/50000 (37%)]\tLoss: 0.009838, Accuracy: 99.61\n",
      "Train Epoch: 113 [17920/50000 (40%)]\tLoss: 0.013160, Accuracy: 99.61\n",
      "Train Epoch: 113 [19200/50000 (43%)]\tLoss: 0.028185, Accuracy: 98.83\n",
      "Train Epoch: 113 [20480/50000 (45%)]\tLoss: 0.038027, Accuracy: 98.44\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 113 [21760/50000 (48%)]\tLoss: 0.022632, Accuracy: 99.22\n",
      "Train Epoch: 113 [23040/50000 (51%)]\tLoss: 0.021427, Accuracy: 99.22\n",
      "Train Epoch: 113 [24320/50000 (54%)]\tLoss: 0.055363, Accuracy: 98.05\n",
      "Train Epoch: 113 [25600/50000 (57%)]\tLoss: 0.027771, Accuracy: 99.22\n",
      "Train Epoch: 113 [26880/50000 (60%)]\tLoss: 0.008375, Accuracy: 100.00\n",
      "Train Epoch: 113 [28160/50000 (62%)]\tLoss: 0.020325, Accuracy: 99.22\n",
      "Train Epoch: 113 [29440/50000 (65%)]\tLoss: 0.019705, Accuracy: 99.22\n",
      "Train Epoch: 113 [30720/50000 (68%)]\tLoss: 0.010811, Accuracy: 99.61\n",
      "Train Epoch: 113 [32000/50000 (71%)]\tLoss: 0.029079, Accuracy: 98.44\n",
      "Train Epoch: 113 [33280/50000 (74%)]\tLoss: 0.035946, Accuracy: 98.83\n",
      "Train Epoch: 113 [34560/50000 (77%)]\tLoss: 0.010094, Accuracy: 99.61\n",
      "Train Epoch: 113 [35840/50000 (80%)]\tLoss: 0.028060, Accuracy: 99.22\n",
      "Train Epoch: 113 [37120/50000 (82%)]\tLoss: 0.039910, Accuracy: 97.66\n",
      "Train Epoch: 113 [38400/50000 (85%)]\tLoss: 0.016998, Accuracy: 99.22\n",
      "Train Epoch: 113 [39680/50000 (88%)]\tLoss: 0.019919, Accuracy: 99.22\n",
      "Train Epoch: 113 [40960/50000 (91%)]\tLoss: 0.032183, Accuracy: 98.44\n",
      "Train Epoch: 113 [42240/50000 (94%)]\tLoss: 0.012120, Accuracy: 99.61\n",
      "Train Epoch: 113 [43520/50000 (97%)]\tLoss: 0.033587, Accuracy: 98.44\n",
      "Train Epoch: 113 [35000/50000 (99%)]\tLoss: 0.022541, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5572, Accuracy: 4465/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.34779667854309 s]\n",
      "Train Epoch: 114 [0/50000 (0%)]\tLoss: 0.019344, Accuracy: 99.61\n",
      "Train Epoch: 114 [1280/50000 (3%)]\tLoss: 0.015127, Accuracy: 99.61\n",
      "Train Epoch: 114 [2560/50000 (6%)]\tLoss: 0.050889, Accuracy: 97.66\n",
      "Train Epoch: 114 [3840/50000 (9%)]\tLoss: 0.017493, Accuracy: 98.83\n",
      "Train Epoch: 114 [5120/50000 (11%)]\tLoss: 0.013352, Accuracy: 99.61\n",
      "Train Epoch: 114 [6400/50000 (14%)]\tLoss: 0.019441, Accuracy: 99.61\n",
      "Train Epoch: 114 [7680/50000 (17%)]\tLoss: 0.008327, Accuracy: 100.00\n",
      "Train Epoch: 114 [8960/50000 (20%)]\tLoss: 0.050029, Accuracy: 98.05\n",
      "Train Epoch: 114 [10240/50000 (23%)]\tLoss: 0.013271, Accuracy: 99.61\n",
      "Train Epoch: 114 [11520/50000 (26%)]\tLoss: 0.011257, Accuracy: 100.00\n",
      "Train Epoch: 114 [12800/50000 (28%)]\tLoss: 0.019737, Accuracy: 98.83\n",
      "Train Epoch: 114 [14080/50000 (31%)]\tLoss: 0.033231, Accuracy: 98.44\n",
      "Train Epoch: 114 [15360/50000 (34%)]\tLoss: 0.028783, Accuracy: 99.22\n",
      "Train Epoch: 114 [16640/50000 (37%)]\tLoss: 0.014854, Accuracy: 99.22\n",
      "Train Epoch: 114 [17920/50000 (40%)]\tLoss: 0.004434, Accuracy: 100.00\n",
      "Train Epoch: 114 [19200/50000 (43%)]\tLoss: 0.010113, Accuracy: 99.61\n",
      "Train Epoch: 114 [20480/50000 (45%)]\tLoss: 0.032527, Accuracy: 98.83\n",
      "Train Epoch: 114 [21760/50000 (48%)]\tLoss: 0.008405, Accuracy: 100.00\n",
      "Train Epoch: 114 [23040/50000 (51%)]\tLoss: 0.042496, Accuracy: 98.44\n",
      "Train Epoch: 114 [24320/50000 (54%)]\tLoss: 0.013664, Accuracy: 99.61\n",
      "Train Epoch: 114 [25600/50000 (57%)]\tLoss: 0.028555, Accuracy: 99.22\n",
      "Train Epoch: 114 [26880/50000 (60%)]\tLoss: 0.043572, Accuracy: 98.83\n",
      "Train Epoch: 114 [28160/50000 (62%)]\tLoss: 0.051327, Accuracy: 98.44\n",
      "Train Epoch: 114 [29440/50000 (65%)]\tLoss: 0.004168, Accuracy: 100.00\n",
      "Train Epoch: 114 [30720/50000 (68%)]\tLoss: 0.030523, Accuracy: 99.22\n",
      "Train Epoch: 114 [32000/50000 (71%)]\tLoss: 0.014644, Accuracy: 99.22\n",
      "Train Epoch: 114 [33280/50000 (74%)]\tLoss: 0.021863, Accuracy: 98.83\n",
      "Train Epoch: 114 [34560/50000 (77%)]\tLoss: 0.019622, Accuracy: 99.22\n",
      "Train Epoch: 114 [35840/50000 (80%)]\tLoss: 0.034334, Accuracy: 97.66\n",
      "Train Epoch: 114 [37120/50000 (82%)]\tLoss: 0.050692, Accuracy: 98.05\n",
      "Train Epoch: 114 [38400/50000 (85%)]\tLoss: 0.028661, Accuracy: 99.22\n",
      "Train Epoch: 114 [39680/50000 (88%)]\tLoss: 0.053247, Accuracy: 99.22\n",
      "Train Epoch: 114 [40960/50000 (91%)]\tLoss: 0.021089, Accuracy: 99.61\n",
      "Train Epoch: 114 [42240/50000 (94%)]\tLoss: 0.005801, Accuracy: 100.00\n",
      "Train Epoch: 114 [43520/50000 (97%)]\tLoss: 0.025054, Accuracy: 99.61\n",
      "Train Epoch: 114 [35000/50000 (99%)]\tLoss: 0.027981, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5499, Accuracy: 4461/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.3593270778656 s]\n",
      "Train Epoch: 115 [0/50000 (0%)]\tLoss: 0.026575, Accuracy: 99.61\n",
      "Train Epoch: 115 [1280/50000 (3%)]\tLoss: 0.018003, Accuracy: 99.61\n",
      "Train Epoch: 115 [2560/50000 (6%)]\tLoss: 0.027374, Accuracy: 98.83\n",
      "Train Epoch: 115 [3840/50000 (9%)]\tLoss: 0.012494, Accuracy: 99.61\n",
      "Train Epoch: 115 [5120/50000 (11%)]\tLoss: 0.044699, Accuracy: 98.83\n",
      "Train Epoch: 115 [6400/50000 (14%)]\tLoss: 0.061191, Accuracy: 97.27\n",
      "Train Epoch: 115 [7680/50000 (17%)]\tLoss: 0.030891, Accuracy: 98.83\n",
      "Train Epoch: 115 [8960/50000 (20%)]\tLoss: 0.025572, Accuracy: 99.22\n",
      "Train Epoch: 115 [10240/50000 (23%)]\tLoss: 0.043277, Accuracy: 98.83\n",
      "Train Epoch: 115 [11520/50000 (26%)]\tLoss: 0.032522, Accuracy: 99.22\n",
      "Train Epoch: 115 [12800/50000 (28%)]\tLoss: 0.014874, Accuracy: 99.22\n",
      "Train Epoch: 115 [14080/50000 (31%)]\tLoss: 0.014959, Accuracy: 99.61\n",
      "Train Epoch: 115 [15360/50000 (34%)]\tLoss: 0.018789, Accuracy: 99.22\n",
      "Train Epoch: 115 [16640/50000 (37%)]\tLoss: 0.034686, Accuracy: 98.44\n",
      "Train Epoch: 115 [17920/50000 (40%)]\tLoss: 0.017980, Accuracy: 99.22\n",
      "Train Epoch: 115 [19200/50000 (43%)]\tLoss: 0.025181, Accuracy: 99.22\n",
      "Train Epoch: 115 [20480/50000 (45%)]\tLoss: 0.010033, Accuracy: 100.00\n",
      "Train Epoch: 115 [21760/50000 (48%)]\tLoss: 0.026907, Accuracy: 98.44\n",
      "Train Epoch: 115 [23040/50000 (51%)]\tLoss: 0.033388, Accuracy: 98.44\n",
      "Train Epoch: 115 [24320/50000 (54%)]\tLoss: 0.031763, Accuracy: 98.44\n",
      "Train Epoch: 115 [25600/50000 (57%)]\tLoss: 0.015595, Accuracy: 100.00\n",
      "Train Epoch: 115 [26880/50000 (60%)]\tLoss: 0.038006, Accuracy: 98.83\n",
      "Train Epoch: 115 [28160/50000 (62%)]\tLoss: 0.019059, Accuracy: 100.00\n",
      "Train Epoch: 115 [29440/50000 (65%)]\tLoss: 0.030093, Accuracy: 99.22\n",
      "Train Epoch: 115 [30720/50000 (68%)]\tLoss: 0.025638, Accuracy: 99.22\n",
      "Train Epoch: 115 [32000/50000 (71%)]\tLoss: 0.039747, Accuracy: 98.83\n",
      "Train Epoch: 115 [33280/50000 (74%)]\tLoss: 0.014759, Accuracy: 99.61\n",
      "Train Epoch: 115 [34560/50000 (77%)]\tLoss: 0.043139, Accuracy: 98.44\n",
      "Train Epoch: 115 [35840/50000 (80%)]\tLoss: 0.012816, Accuracy: 100.00\n",
      "Train Epoch: 115 [37120/50000 (82%)]\tLoss: 0.045218, Accuracy: 98.83\n",
      "Train Epoch: 115 [38400/50000 (85%)]\tLoss: 0.003210, Accuracy: 100.00\n",
      "Train Epoch: 115 [39680/50000 (88%)]\tLoss: 0.014644, Accuracy: 99.61\n",
      "Train Epoch: 115 [40960/50000 (91%)]\tLoss: 0.016889, Accuracy: 99.22\n",
      "Train Epoch: 115 [42240/50000 (94%)]\tLoss: 0.021982, Accuracy: 98.83\n",
      "Train Epoch: 115 [43520/50000 (97%)]\tLoss: 0.018350, Accuracy: 100.00\n",
      "Train Epoch: 115 [35000/50000 (99%)]\tLoss: 0.032828, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5660, Accuracy: 4469/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.360713958740234 s]\n",
      "Train Epoch: 116 [0/50000 (0%)]\tLoss: 0.022398, Accuracy: 98.83\n",
      "Train Epoch: 116 [1280/50000 (3%)]\tLoss: 0.022271, Accuracy: 99.61\n",
      "Train Epoch: 116 [2560/50000 (6%)]\tLoss: 0.030575, Accuracy: 99.22\n",
      "Train Epoch: 116 [3840/50000 (9%)]\tLoss: 0.055218, Accuracy: 98.05\n",
      "Train Epoch: 116 [5120/50000 (11%)]\tLoss: 0.025396, Accuracy: 99.61\n",
      "Train Epoch: 116 [6400/50000 (14%)]\tLoss: 0.047226, Accuracy: 98.44\n",
      "Train Epoch: 116 [7680/50000 (17%)]\tLoss: 0.015430, Accuracy: 99.61\n",
      "Train Epoch: 116 [8960/50000 (20%)]\tLoss: 0.033189, Accuracy: 99.22\n",
      "Train Epoch: 116 [10240/50000 (23%)]\tLoss: 0.006936, Accuracy: 100.00\n",
      "Train Epoch: 116 [11520/50000 (26%)]\tLoss: 0.017259, Accuracy: 99.22\n",
      "Train Epoch: 116 [12800/50000 (28%)]\tLoss: 0.024997, Accuracy: 98.44\n",
      "Train Epoch: 116 [14080/50000 (31%)]\tLoss: 0.019996, Accuracy: 99.22\n",
      "Train Epoch: 116 [15360/50000 (34%)]\tLoss: 0.022559, Accuracy: 98.83\n",
      "Train Epoch: 116 [16640/50000 (37%)]\tLoss: 0.031342, Accuracy: 99.22\n",
      "Train Epoch: 116 [17920/50000 (40%)]\tLoss: 0.052876, Accuracy: 97.66\n",
      "Train Epoch: 116 [19200/50000 (43%)]\tLoss: 0.021444, Accuracy: 98.83\n",
      "Train Epoch: 116 [20480/50000 (45%)]\tLoss: 0.016416, Accuracy: 100.00\n",
      "Train Epoch: 116 [21760/50000 (48%)]\tLoss: 0.014796, Accuracy: 99.22\n",
      "Train Epoch: 116 [23040/50000 (51%)]\tLoss: 0.038120, Accuracy: 98.83\n",
      "Train Epoch: 116 [24320/50000 (54%)]\tLoss: 0.018960, Accuracy: 99.22\n",
      "Train Epoch: 116 [25600/50000 (57%)]\tLoss: 0.038096, Accuracy: 98.83\n",
      "Train Epoch: 116 [26880/50000 (60%)]\tLoss: 0.026162, Accuracy: 98.44\n",
      "Train Epoch: 116 [28160/50000 (62%)]\tLoss: 0.020628, Accuracy: 99.61\n",
      "Train Epoch: 116 [29440/50000 (65%)]\tLoss: 0.039705, Accuracy: 98.83\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 116 [30720/50000 (68%)]\tLoss: 0.022763, Accuracy: 98.83\n",
      "Train Epoch: 116 [32000/50000 (71%)]\tLoss: 0.025785, Accuracy: 98.83\n",
      "Train Epoch: 116 [33280/50000 (74%)]\tLoss: 0.008494, Accuracy: 100.00\n",
      "Train Epoch: 116 [34560/50000 (77%)]\tLoss: 0.038253, Accuracy: 98.83\n",
      "Train Epoch: 116 [35840/50000 (80%)]\tLoss: 0.009921, Accuracy: 100.00\n",
      "Train Epoch: 116 [37120/50000 (82%)]\tLoss: 0.014694, Accuracy: 99.61\n",
      "Train Epoch: 116 [38400/50000 (85%)]\tLoss: 0.050948, Accuracy: 98.83\n",
      "Train Epoch: 116 [39680/50000 (88%)]\tLoss: 0.052853, Accuracy: 98.44\n",
      "Train Epoch: 116 [40960/50000 (91%)]\tLoss: 0.021104, Accuracy: 99.22\n",
      "Train Epoch: 116 [42240/50000 (94%)]\tLoss: 0.014451, Accuracy: 99.22\n",
      "Train Epoch: 116 [43520/50000 (97%)]\tLoss: 0.022793, Accuracy: 99.22\n",
      "Train Epoch: 116 [35000/50000 (99%)]\tLoss: 0.034058, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5579, Accuracy: 4472/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.38651704788208 s]\n",
      "Train Epoch: 117 [0/50000 (0%)]\tLoss: 0.037737, Accuracy: 98.05\n",
      "Train Epoch: 117 [1280/50000 (3%)]\tLoss: 0.022390, Accuracy: 99.22\n",
      "Train Epoch: 117 [2560/50000 (6%)]\tLoss: 0.022654, Accuracy: 98.44\n",
      "Train Epoch: 117 [3840/50000 (9%)]\tLoss: 0.012195, Accuracy: 99.61\n",
      "Train Epoch: 117 [5120/50000 (11%)]\tLoss: 0.017079, Accuracy: 99.61\n",
      "Train Epoch: 117 [6400/50000 (14%)]\tLoss: 0.021228, Accuracy: 99.61\n",
      "Train Epoch: 117 [7680/50000 (17%)]\tLoss: 0.012796, Accuracy: 99.22\n",
      "Train Epoch: 117 [8960/50000 (20%)]\tLoss: 0.013929, Accuracy: 99.61\n",
      "Train Epoch: 117 [10240/50000 (23%)]\tLoss: 0.012345, Accuracy: 99.61\n",
      "Train Epoch: 117 [11520/50000 (26%)]\tLoss: 0.035259, Accuracy: 98.44\n",
      "Train Epoch: 117 [12800/50000 (28%)]\tLoss: 0.020717, Accuracy: 98.83\n",
      "Train Epoch: 117 [14080/50000 (31%)]\tLoss: 0.010161, Accuracy: 99.61\n",
      "Train Epoch: 117 [15360/50000 (34%)]\tLoss: 0.043454, Accuracy: 98.83\n",
      "Train Epoch: 117 [16640/50000 (37%)]\tLoss: 0.020810, Accuracy: 99.22\n",
      "Train Epoch: 117 [17920/50000 (40%)]\tLoss: 0.022489, Accuracy: 99.61\n",
      "Train Epoch: 117 [19200/50000 (43%)]\tLoss: 0.042826, Accuracy: 98.05\n",
      "Train Epoch: 117 [20480/50000 (45%)]\tLoss: 0.010874, Accuracy: 100.00\n",
      "Train Epoch: 117 [21760/50000 (48%)]\tLoss: 0.034925, Accuracy: 98.83\n",
      "Train Epoch: 117 [23040/50000 (51%)]\tLoss: 0.083934, Accuracy: 98.44\n",
      "Train Epoch: 117 [24320/50000 (54%)]\tLoss: 0.023080, Accuracy: 99.22\n",
      "Train Epoch: 117 [25600/50000 (57%)]\tLoss: 0.025361, Accuracy: 99.22\n",
      "Train Epoch: 117 [26880/50000 (60%)]\tLoss: 0.023963, Accuracy: 98.83\n",
      "Train Epoch: 117 [28160/50000 (62%)]\tLoss: 0.005840, Accuracy: 100.00\n",
      "Train Epoch: 117 [29440/50000 (65%)]\tLoss: 0.022209, Accuracy: 98.83\n",
      "Train Epoch: 117 [30720/50000 (68%)]\tLoss: 0.016033, Accuracy: 99.61\n",
      "Train Epoch: 117 [32000/50000 (71%)]\tLoss: 0.012683, Accuracy: 99.61\n",
      "Train Epoch: 117 [33280/50000 (74%)]\tLoss: 0.031759, Accuracy: 98.83\n",
      "Train Epoch: 117 [34560/50000 (77%)]\tLoss: 0.012112, Accuracy: 99.61\n",
      "Train Epoch: 117 [35840/50000 (80%)]\tLoss: 0.013144, Accuracy: 100.00\n",
      "Train Epoch: 117 [37120/50000 (82%)]\tLoss: 0.010286, Accuracy: 100.00\n",
      "Train Epoch: 117 [38400/50000 (85%)]\tLoss: 0.021844, Accuracy: 99.61\n",
      "Train Epoch: 117 [39680/50000 (88%)]\tLoss: 0.030306, Accuracy: 98.83\n",
      "Train Epoch: 117 [40960/50000 (91%)]\tLoss: 0.040446, Accuracy: 98.83\n",
      "Train Epoch: 117 [42240/50000 (94%)]\tLoss: 0.024522, Accuracy: 99.22\n",
      "Train Epoch: 117 [43520/50000 (97%)]\tLoss: 0.021773, Accuracy: 98.83\n",
      "Train Epoch: 117 [35000/50000 (99%)]\tLoss: 0.014273, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5570, Accuracy: 4471/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.339639902114868 s]\n",
      "Train Epoch: 118 [0/50000 (0%)]\tLoss: 0.038626, Accuracy: 98.44\n",
      "Train Epoch: 118 [1280/50000 (3%)]\tLoss: 0.010067, Accuracy: 100.00\n",
      "Train Epoch: 118 [2560/50000 (6%)]\tLoss: 0.008139, Accuracy: 99.61\n",
      "Train Epoch: 118 [3840/50000 (9%)]\tLoss: 0.038098, Accuracy: 98.83\n",
      "Train Epoch: 118 [5120/50000 (11%)]\tLoss: 0.030067, Accuracy: 98.83\n",
      "Train Epoch: 118 [6400/50000 (14%)]\tLoss: 0.015779, Accuracy: 99.61\n",
      "Train Epoch: 118 [7680/50000 (17%)]\tLoss: 0.039931, Accuracy: 99.22\n",
      "Train Epoch: 118 [8960/50000 (20%)]\tLoss: 0.018619, Accuracy: 99.22\n",
      "Train Epoch: 118 [10240/50000 (23%)]\tLoss: 0.019685, Accuracy: 99.61\n",
      "Train Epoch: 118 [11520/50000 (26%)]\tLoss: 0.033389, Accuracy: 97.66\n",
      "Train Epoch: 118 [12800/50000 (28%)]\tLoss: 0.033967, Accuracy: 98.05\n",
      "Train Epoch: 118 [14080/50000 (31%)]\tLoss: 0.027284, Accuracy: 99.22\n",
      "Train Epoch: 118 [15360/50000 (34%)]\tLoss: 0.011846, Accuracy: 99.61\n",
      "Train Epoch: 118 [16640/50000 (37%)]\tLoss: 0.036568, Accuracy: 99.22\n",
      "Train Epoch: 118 [17920/50000 (40%)]\tLoss: 0.021199, Accuracy: 99.61\n",
      "Train Epoch: 118 [19200/50000 (43%)]\tLoss: 0.028170, Accuracy: 98.83\n",
      "Train Epoch: 118 [20480/50000 (45%)]\tLoss: 0.018981, Accuracy: 99.22\n",
      "Train Epoch: 118 [21760/50000 (48%)]\tLoss: 0.008947, Accuracy: 100.00\n",
      "Train Epoch: 118 [23040/50000 (51%)]\tLoss: 0.033268, Accuracy: 99.22\n",
      "Train Epoch: 118 [24320/50000 (54%)]\tLoss: 0.051146, Accuracy: 98.05\n",
      "Train Epoch: 118 [25600/50000 (57%)]\tLoss: 0.007584, Accuracy: 100.00\n",
      "Train Epoch: 118 [26880/50000 (60%)]\tLoss: 0.021266, Accuracy: 99.22\n",
      "Train Epoch: 118 [28160/50000 (62%)]\tLoss: 0.011323, Accuracy: 100.00\n",
      "Train Epoch: 118 [29440/50000 (65%)]\tLoss: 0.024644, Accuracy: 98.83\n",
      "Train Epoch: 118 [30720/50000 (68%)]\tLoss: 0.042525, Accuracy: 98.83\n",
      "Train Epoch: 118 [32000/50000 (71%)]\tLoss: 0.019212, Accuracy: 99.61\n",
      "Train Epoch: 118 [33280/50000 (74%)]\tLoss: 0.010991, Accuracy: 99.61\n",
      "Train Epoch: 118 [34560/50000 (77%)]\tLoss: 0.020674, Accuracy: 99.22\n",
      "Train Epoch: 118 [35840/50000 (80%)]\tLoss: 0.007165, Accuracy: 100.00\n",
      "Train Epoch: 118 [37120/50000 (82%)]\tLoss: 0.025426, Accuracy: 99.22\n",
      "Train Epoch: 118 [38400/50000 (85%)]\tLoss: 0.058441, Accuracy: 98.05\n",
      "Train Epoch: 118 [39680/50000 (88%)]\tLoss: 0.014021, Accuracy: 99.61\n",
      "Train Epoch: 118 [40960/50000 (91%)]\tLoss: 0.019862, Accuracy: 98.83\n",
      "Train Epoch: 118 [42240/50000 (94%)]\tLoss: 0.026532, Accuracy: 98.83\n",
      "Train Epoch: 118 [43520/50000 (97%)]\tLoss: 0.042108, Accuracy: 98.44\n",
      "Train Epoch: 118 [35000/50000 (99%)]\tLoss: 0.011440, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5490, Accuracy: 4480/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.31504535675049 s]\n",
      "Train Epoch: 119 [0/50000 (0%)]\tLoss: 0.041461, Accuracy: 98.44\n",
      "Train Epoch: 119 [1280/50000 (3%)]\tLoss: 0.029872, Accuracy: 98.83\n",
      "Train Epoch: 119 [2560/50000 (6%)]\tLoss: 0.004043, Accuracy: 100.00\n",
      "Train Epoch: 119 [3840/50000 (9%)]\tLoss: 0.019095, Accuracy: 98.83\n",
      "Train Epoch: 119 [5120/50000 (11%)]\tLoss: 0.011365, Accuracy: 100.00\n",
      "Train Epoch: 119 [6400/50000 (14%)]\tLoss: 0.007881, Accuracy: 100.00\n",
      "Train Epoch: 119 [7680/50000 (17%)]\tLoss: 0.038895, Accuracy: 98.05\n",
      "Train Epoch: 119 [8960/50000 (20%)]\tLoss: 0.016851, Accuracy: 99.22\n",
      "Train Epoch: 119 [10240/50000 (23%)]\tLoss: 0.028502, Accuracy: 98.44\n",
      "Train Epoch: 119 [11520/50000 (26%)]\tLoss: 0.026860, Accuracy: 99.61\n",
      "Train Epoch: 119 [12800/50000 (28%)]\tLoss: 0.034371, Accuracy: 98.83\n",
      "Train Epoch: 119 [14080/50000 (31%)]\tLoss: 0.024541, Accuracy: 99.61\n",
      "Train Epoch: 119 [15360/50000 (34%)]\tLoss: 0.033170, Accuracy: 98.83\n",
      "Train Epoch: 119 [16640/50000 (37%)]\tLoss: 0.018986, Accuracy: 99.22\n",
      "Train Epoch: 119 [17920/50000 (40%)]\tLoss: 0.017136, Accuracy: 99.22\n",
      "Train Epoch: 119 [19200/50000 (43%)]\tLoss: 0.020589, Accuracy: 99.22\n",
      "Train Epoch: 119 [20480/50000 (45%)]\tLoss: 0.013708, Accuracy: 99.61\n",
      "Train Epoch: 119 [21760/50000 (48%)]\tLoss: 0.024125, Accuracy: 99.22\n",
      "Train Epoch: 119 [23040/50000 (51%)]\tLoss: 0.022380, Accuracy: 99.22\n",
      "Train Epoch: 119 [24320/50000 (54%)]\tLoss: 0.020843, Accuracy: 99.22\n",
      "Train Epoch: 119 [25600/50000 (57%)]\tLoss: 0.026300, Accuracy: 98.83\n",
      "Train Epoch: 119 [26880/50000 (60%)]\tLoss: 0.043603, Accuracy: 98.44\n",
      "Train Epoch: 119 [28160/50000 (62%)]\tLoss: 0.012311, Accuracy: 99.22\n",
      "Train Epoch: 119 [29440/50000 (65%)]\tLoss: 0.020512, Accuracy: 99.22\n",
      "Train Epoch: 119 [30720/50000 (68%)]\tLoss: 0.018700, Accuracy: 99.61\n",
      "Train Epoch: 119 [32000/50000 (71%)]\tLoss: 0.042951, Accuracy: 98.05\n",
      "Train Epoch: 119 [33280/50000 (74%)]\tLoss: 0.039933, Accuracy: 98.83\n",
      "Train Epoch: 119 [34560/50000 (77%)]\tLoss: 0.011892, Accuracy: 99.61\n",
      "Train Epoch: 119 [35840/50000 (80%)]\tLoss: 0.029058, Accuracy: 99.22\n",
      "Train Epoch: 119 [37120/50000 (82%)]\tLoss: 0.017874, Accuracy: 99.61\n",
      "Train Epoch: 119 [38400/50000 (85%)]\tLoss: 0.031889, Accuracy: 98.83\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 119 [39680/50000 (88%)]\tLoss: 0.038174, Accuracy: 98.44\n",
      "Train Epoch: 119 [40960/50000 (91%)]\tLoss: 0.010043, Accuracy: 99.61\n",
      "Train Epoch: 119 [42240/50000 (94%)]\tLoss: 0.018556, Accuracy: 99.61\n",
      "Train Epoch: 119 [43520/50000 (97%)]\tLoss: 0.025061, Accuracy: 99.22\n",
      "Train Epoch: 119 [35000/50000 (99%)]\tLoss: 0.045473, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5536, Accuracy: 4467/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.31070899963379 s]\n",
      "Train Epoch: 120 [0/50000 (0%)]\tLoss: 0.032849, Accuracy: 98.83\n",
      "Train Epoch: 120 [1280/50000 (3%)]\tLoss: 0.041201, Accuracy: 98.05\n",
      "Train Epoch: 120 [2560/50000 (6%)]\tLoss: 0.012645, Accuracy: 99.22\n",
      "Train Epoch: 120 [3840/50000 (9%)]\tLoss: 0.046098, Accuracy: 98.44\n",
      "Train Epoch: 120 [5120/50000 (11%)]\tLoss: 0.038470, Accuracy: 99.22\n",
      "Train Epoch: 120 [6400/50000 (14%)]\tLoss: 0.008021, Accuracy: 100.00\n",
      "Train Epoch: 120 [7680/50000 (17%)]\tLoss: 0.013367, Accuracy: 99.61\n",
      "Train Epoch: 120 [8960/50000 (20%)]\tLoss: 0.026152, Accuracy: 99.61\n",
      "Train Epoch: 120 [10240/50000 (23%)]\tLoss: 0.018422, Accuracy: 99.22\n",
      "Train Epoch: 120 [11520/50000 (26%)]\tLoss: 0.021349, Accuracy: 99.22\n",
      "Train Epoch: 120 [12800/50000 (28%)]\tLoss: 0.005418, Accuracy: 100.00\n",
      "Train Epoch: 120 [14080/50000 (31%)]\tLoss: 0.024123, Accuracy: 98.44\n",
      "Train Epoch: 120 [15360/50000 (34%)]\tLoss: 0.025575, Accuracy: 98.83\n",
      "Train Epoch: 120 [16640/50000 (37%)]\tLoss: 0.012991, Accuracy: 99.61\n",
      "Train Epoch: 120 [17920/50000 (40%)]\tLoss: 0.009049, Accuracy: 99.61\n",
      "Train Epoch: 120 [19200/50000 (43%)]\tLoss: 0.044746, Accuracy: 97.66\n",
      "Train Epoch: 120 [20480/50000 (45%)]\tLoss: 0.051543, Accuracy: 96.88\n",
      "Train Epoch: 120 [21760/50000 (48%)]\tLoss: 0.014777, Accuracy: 99.22\n",
      "Train Epoch: 120 [23040/50000 (51%)]\tLoss: 0.009167, Accuracy: 99.61\n",
      "Train Epoch: 120 [24320/50000 (54%)]\tLoss: 0.062200, Accuracy: 98.05\n",
      "Train Epoch: 120 [25600/50000 (57%)]\tLoss: 0.039957, Accuracy: 98.44\n",
      "Train Epoch: 120 [26880/50000 (60%)]\tLoss: 0.008650, Accuracy: 100.00\n",
      "Train Epoch: 120 [28160/50000 (62%)]\tLoss: 0.053323, Accuracy: 98.05\n",
      "Train Epoch: 120 [29440/50000 (65%)]\tLoss: 0.015166, Accuracy: 99.22\n",
      "Train Epoch: 120 [30720/50000 (68%)]\tLoss: 0.061925, Accuracy: 96.88\n",
      "Train Epoch: 120 [32000/50000 (71%)]\tLoss: 0.021066, Accuracy: 99.61\n",
      "Train Epoch: 120 [33280/50000 (74%)]\tLoss: 0.016562, Accuracy: 100.00\n",
      "Train Epoch: 120 [34560/50000 (77%)]\tLoss: 0.052872, Accuracy: 97.66\n",
      "Train Epoch: 120 [35840/50000 (80%)]\tLoss: 0.019162, Accuracy: 98.83\n",
      "Train Epoch: 120 [37120/50000 (82%)]\tLoss: 0.011288, Accuracy: 99.61\n",
      "Train Epoch: 120 [38400/50000 (85%)]\tLoss: 0.015619, Accuracy: 99.61\n",
      "Train Epoch: 120 [39680/50000 (88%)]\tLoss: 0.026235, Accuracy: 99.22\n",
      "Train Epoch: 120 [40960/50000 (91%)]\tLoss: 0.035696, Accuracy: 98.44\n",
      "Train Epoch: 120 [42240/50000 (94%)]\tLoss: 0.009960, Accuracy: 100.00\n",
      "Train Epoch: 120 [43520/50000 (97%)]\tLoss: 0.016399, Accuracy: 99.22\n",
      "Train Epoch: 120 [35000/50000 (99%)]\tLoss: 0.014290, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5592, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35096764564514 s]\n",
      "Train Epoch: 121 [0/50000 (0%)]\tLoss: 0.041526, Accuracy: 99.22\n",
      "Train Epoch: 121 [1280/50000 (3%)]\tLoss: 0.016202, Accuracy: 99.22\n",
      "Train Epoch: 121 [2560/50000 (6%)]\tLoss: 0.014981, Accuracy: 99.61\n",
      "Train Epoch: 121 [3840/50000 (9%)]\tLoss: 0.036335, Accuracy: 98.44\n",
      "Train Epoch: 121 [5120/50000 (11%)]\tLoss: 0.046315, Accuracy: 99.22\n",
      "Train Epoch: 121 [6400/50000 (14%)]\tLoss: 0.032065, Accuracy: 99.22\n",
      "Train Epoch: 121 [7680/50000 (17%)]\tLoss: 0.059151, Accuracy: 98.83\n",
      "Train Epoch: 121 [8960/50000 (20%)]\tLoss: 0.010587, Accuracy: 99.61\n",
      "Train Epoch: 121 [10240/50000 (23%)]\tLoss: 0.008477, Accuracy: 100.00\n",
      "Train Epoch: 121 [11520/50000 (26%)]\tLoss: 0.013544, Accuracy: 99.61\n",
      "Train Epoch: 121 [12800/50000 (28%)]\tLoss: 0.022419, Accuracy: 99.22\n",
      "Train Epoch: 121 [14080/50000 (31%)]\tLoss: 0.032611, Accuracy: 99.61\n",
      "Train Epoch: 121 [15360/50000 (34%)]\tLoss: 0.019572, Accuracy: 99.22\n",
      "Train Epoch: 121 [16640/50000 (37%)]\tLoss: 0.032037, Accuracy: 98.83\n",
      "Train Epoch: 121 [17920/50000 (40%)]\tLoss: 0.013812, Accuracy: 99.22\n",
      "Train Epoch: 121 [19200/50000 (43%)]\tLoss: 0.020229, Accuracy: 99.22\n",
      "Train Epoch: 121 [20480/50000 (45%)]\tLoss: 0.032543, Accuracy: 98.44\n",
      "Train Epoch: 121 [21760/50000 (48%)]\tLoss: 0.048188, Accuracy: 99.22\n",
      "Train Epoch: 121 [23040/50000 (51%)]\tLoss: 0.022122, Accuracy: 99.61\n",
      "Train Epoch: 121 [24320/50000 (54%)]\tLoss: 0.009966, Accuracy: 99.61\n",
      "Train Epoch: 121 [25600/50000 (57%)]\tLoss: 0.006406, Accuracy: 100.00\n",
      "Train Epoch: 121 [26880/50000 (60%)]\tLoss: 0.021292, Accuracy: 98.83\n",
      "Train Epoch: 121 [28160/50000 (62%)]\tLoss: 0.012126, Accuracy: 99.61\n",
      "Train Epoch: 121 [29440/50000 (65%)]\tLoss: 0.022965, Accuracy: 99.22\n",
      "Train Epoch: 121 [30720/50000 (68%)]\tLoss: 0.026084, Accuracy: 98.44\n",
      "Train Epoch: 121 [32000/50000 (71%)]\tLoss: 0.023049, Accuracy: 99.22\n",
      "Train Epoch: 121 [33280/50000 (74%)]\tLoss: 0.037205, Accuracy: 98.83\n",
      "Train Epoch: 121 [34560/50000 (77%)]\tLoss: 0.036562, Accuracy: 98.83\n",
      "Train Epoch: 121 [35840/50000 (80%)]\tLoss: 0.071232, Accuracy: 96.88\n",
      "Train Epoch: 121 [37120/50000 (82%)]\tLoss: 0.019166, Accuracy: 99.22\n",
      "Train Epoch: 121 [38400/50000 (85%)]\tLoss: 0.033804, Accuracy: 99.61\n",
      "Train Epoch: 121 [39680/50000 (88%)]\tLoss: 0.043014, Accuracy: 99.22\n",
      "Train Epoch: 121 [40960/50000 (91%)]\tLoss: 0.031607, Accuracy: 98.83\n",
      "Train Epoch: 121 [42240/50000 (94%)]\tLoss: 0.014800, Accuracy: 99.22\n",
      "Train Epoch: 121 [43520/50000 (97%)]\tLoss: 0.030663, Accuracy: 98.05\n",
      "Train Epoch: 121 [35000/50000 (99%)]\tLoss: 0.038529, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5492, Accuracy: 4470/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35941243171692 s]\n",
      "Train Epoch: 122 [0/50000 (0%)]\tLoss: 0.016778, Accuracy: 99.61\n",
      "Train Epoch: 122 [1280/50000 (3%)]\tLoss: 0.031686, Accuracy: 98.05\n",
      "Train Epoch: 122 [2560/50000 (6%)]\tLoss: 0.024716, Accuracy: 99.22\n",
      "Train Epoch: 122 [3840/50000 (9%)]\tLoss: 0.023213, Accuracy: 99.22\n",
      "Train Epoch: 122 [5120/50000 (11%)]\tLoss: 0.033642, Accuracy: 98.44\n",
      "Train Epoch: 122 [6400/50000 (14%)]\tLoss: 0.046736, Accuracy: 98.05\n",
      "Train Epoch: 122 [7680/50000 (17%)]\tLoss: 0.007386, Accuracy: 100.00\n",
      "Train Epoch: 122 [8960/50000 (20%)]\tLoss: 0.016397, Accuracy: 99.22\n",
      "Train Epoch: 122 [10240/50000 (23%)]\tLoss: 0.057285, Accuracy: 98.44\n",
      "Train Epoch: 122 [11520/50000 (26%)]\tLoss: 0.027576, Accuracy: 99.22\n",
      "Train Epoch: 122 [12800/50000 (28%)]\tLoss: 0.016657, Accuracy: 99.61\n",
      "Train Epoch: 122 [14080/50000 (31%)]\tLoss: 0.014776, Accuracy: 99.61\n",
      "Train Epoch: 122 [15360/50000 (34%)]\tLoss: 0.008058, Accuracy: 99.61\n",
      "Train Epoch: 122 [16640/50000 (37%)]\tLoss: 0.032820, Accuracy: 98.05\n",
      "Train Epoch: 122 [17920/50000 (40%)]\tLoss: 0.016626, Accuracy: 100.00\n",
      "Train Epoch: 122 [19200/50000 (43%)]\tLoss: 0.009834, Accuracy: 99.61\n",
      "Train Epoch: 122 [20480/50000 (45%)]\tLoss: 0.033882, Accuracy: 98.44\n",
      "Train Epoch: 122 [21760/50000 (48%)]\tLoss: 0.033446, Accuracy: 98.44\n",
      "Train Epoch: 122 [23040/50000 (51%)]\tLoss: 0.035201, Accuracy: 98.44\n",
      "Train Epoch: 122 [24320/50000 (54%)]\tLoss: 0.016127, Accuracy: 99.61\n",
      "Train Epoch: 122 [25600/50000 (57%)]\tLoss: 0.018518, Accuracy: 99.61\n",
      "Train Epoch: 122 [26880/50000 (60%)]\tLoss: 0.014366, Accuracy: 99.61\n",
      "Train Epoch: 122 [28160/50000 (62%)]\tLoss: 0.018005, Accuracy: 99.22\n",
      "Train Epoch: 122 [29440/50000 (65%)]\tLoss: 0.035336, Accuracy: 98.05\n",
      "Train Epoch: 122 [30720/50000 (68%)]\tLoss: 0.049957, Accuracy: 98.83\n",
      "Train Epoch: 122 [32000/50000 (71%)]\tLoss: 0.035029, Accuracy: 98.44\n",
      "Train Epoch: 122 [33280/50000 (74%)]\tLoss: 0.043990, Accuracy: 98.44\n",
      "Train Epoch: 122 [34560/50000 (77%)]\tLoss: 0.006650, Accuracy: 99.61\n",
      "Train Epoch: 122 [35840/50000 (80%)]\tLoss: 0.025177, Accuracy: 98.83\n",
      "Train Epoch: 122 [37120/50000 (82%)]\tLoss: 0.029550, Accuracy: 98.44\n",
      "Train Epoch: 122 [38400/50000 (85%)]\tLoss: 0.014366, Accuracy: 99.61\n",
      "Train Epoch: 122 [39680/50000 (88%)]\tLoss: 0.009263, Accuracy: 99.61\n",
      "Train Epoch: 122 [40960/50000 (91%)]\tLoss: 0.022417, Accuracy: 99.22\n",
      "Train Epoch: 122 [42240/50000 (94%)]\tLoss: 0.021021, Accuracy: 98.83\n",
      "Train Epoch: 122 [43520/50000 (97%)]\tLoss: 0.010442, Accuracy: 99.61\n",
      "Train Epoch: 122 [35000/50000 (99%)]\tLoss: 0.053938, Accuracy: 98.00\n",
      "\n",
      "Validation set: Average loss: 0.5595, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35762333869934 s]\n",
      "Train Epoch: 123 [0/50000 (0%)]\tLoss: 0.018537, Accuracy: 99.61\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 123 [1280/50000 (3%)]\tLoss: 0.014343, Accuracy: 99.22\n",
      "Train Epoch: 123 [2560/50000 (6%)]\tLoss: 0.026045, Accuracy: 98.83\n",
      "Train Epoch: 123 [3840/50000 (9%)]\tLoss: 0.035411, Accuracy: 98.83\n",
      "Train Epoch: 123 [5120/50000 (11%)]\tLoss: 0.008639, Accuracy: 100.00\n",
      "Train Epoch: 123 [6400/50000 (14%)]\tLoss: 0.020385, Accuracy: 99.61\n",
      "Train Epoch: 123 [7680/50000 (17%)]\tLoss: 0.023356, Accuracy: 98.83\n",
      "Train Epoch: 123 [8960/50000 (20%)]\tLoss: 0.023055, Accuracy: 99.22\n",
      "Train Epoch: 123 [10240/50000 (23%)]\tLoss: 0.024162, Accuracy: 98.83\n",
      "Train Epoch: 123 [11520/50000 (26%)]\tLoss: 0.007985, Accuracy: 100.00\n",
      "Train Epoch: 123 [12800/50000 (28%)]\tLoss: 0.009620, Accuracy: 100.00\n",
      "Train Epoch: 123 [14080/50000 (31%)]\tLoss: 0.028996, Accuracy: 98.44\n",
      "Train Epoch: 123 [15360/50000 (34%)]\tLoss: 0.023633, Accuracy: 98.44\n",
      "Train Epoch: 123 [16640/50000 (37%)]\tLoss: 0.018086, Accuracy: 99.22\n",
      "Train Epoch: 123 [17920/50000 (40%)]\tLoss: 0.029520, Accuracy: 98.44\n",
      "Train Epoch: 123 [19200/50000 (43%)]\tLoss: 0.006236, Accuracy: 100.00\n",
      "Train Epoch: 123 [20480/50000 (45%)]\tLoss: 0.033770, Accuracy: 98.83\n",
      "Train Epoch: 123 [21760/50000 (48%)]\tLoss: 0.026459, Accuracy: 99.22\n",
      "Train Epoch: 123 [23040/50000 (51%)]\tLoss: 0.007097, Accuracy: 100.00\n",
      "Train Epoch: 123 [24320/50000 (54%)]\tLoss: 0.023342, Accuracy: 99.61\n",
      "Train Epoch: 123 [25600/50000 (57%)]\tLoss: 0.009822, Accuracy: 100.00\n",
      "Train Epoch: 123 [26880/50000 (60%)]\tLoss: 0.007428, Accuracy: 99.61\n",
      "Train Epoch: 123 [28160/50000 (62%)]\tLoss: 0.009795, Accuracy: 100.00\n",
      "Train Epoch: 123 [29440/50000 (65%)]\tLoss: 0.033676, Accuracy: 98.05\n",
      "Train Epoch: 123 [30720/50000 (68%)]\tLoss: 0.010755, Accuracy: 100.00\n",
      "Train Epoch: 123 [32000/50000 (71%)]\tLoss: 0.018696, Accuracy: 99.22\n",
      "Train Epoch: 123 [33280/50000 (74%)]\tLoss: 0.030795, Accuracy: 98.83\n",
      "Train Epoch: 123 [34560/50000 (77%)]\tLoss: 0.011363, Accuracy: 100.00\n",
      "Train Epoch: 123 [35840/50000 (80%)]\tLoss: 0.030453, Accuracy: 99.22\n",
      "Train Epoch: 123 [37120/50000 (82%)]\tLoss: 0.018602, Accuracy: 99.22\n",
      "Train Epoch: 123 [38400/50000 (85%)]\tLoss: 0.034268, Accuracy: 98.44\n",
      "Train Epoch: 123 [39680/50000 (88%)]\tLoss: 0.052760, Accuracy: 98.05\n",
      "Train Epoch: 123 [40960/50000 (91%)]\tLoss: 0.021861, Accuracy: 99.22\n",
      "Train Epoch: 123 [42240/50000 (94%)]\tLoss: 0.012776, Accuracy: 99.22\n",
      "Train Epoch: 123 [43520/50000 (97%)]\tLoss: 0.008532, Accuracy: 99.61\n",
      "Train Epoch: 123 [35000/50000 (99%)]\tLoss: 0.042358, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5632, Accuracy: 4470/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.38530707359314 s]\n",
      "Train Epoch: 124 [0/50000 (0%)]\tLoss: 0.012377, Accuracy: 99.61\n",
      "Train Epoch: 124 [1280/50000 (3%)]\tLoss: 0.023964, Accuracy: 98.83\n",
      "Train Epoch: 124 [2560/50000 (6%)]\tLoss: 0.013030, Accuracy: 99.61\n",
      "Train Epoch: 124 [3840/50000 (9%)]\tLoss: 0.020036, Accuracy: 98.83\n",
      "Train Epoch: 124 [5120/50000 (11%)]\tLoss: 0.010006, Accuracy: 99.61\n",
      "Train Epoch: 124 [6400/50000 (14%)]\tLoss: 0.024517, Accuracy: 99.61\n",
      "Train Epoch: 124 [7680/50000 (17%)]\tLoss: 0.041378, Accuracy: 98.83\n",
      "Train Epoch: 124 [8960/50000 (20%)]\tLoss: 0.009596, Accuracy: 100.00\n",
      "Train Epoch: 124 [10240/50000 (23%)]\tLoss: 0.051975, Accuracy: 97.66\n",
      "Train Epoch: 124 [11520/50000 (26%)]\tLoss: 0.032792, Accuracy: 98.44\n",
      "Train Epoch: 124 [12800/50000 (28%)]\tLoss: 0.025496, Accuracy: 99.61\n",
      "Train Epoch: 124 [14080/50000 (31%)]\tLoss: 0.039460, Accuracy: 98.83\n",
      "Train Epoch: 124 [15360/50000 (34%)]\tLoss: 0.026781, Accuracy: 99.61\n",
      "Train Epoch: 124 [16640/50000 (37%)]\tLoss: 0.036595, Accuracy: 98.44\n",
      "Train Epoch: 124 [17920/50000 (40%)]\tLoss: 0.016415, Accuracy: 99.61\n",
      "Train Epoch: 124 [19200/50000 (43%)]\tLoss: 0.007526, Accuracy: 100.00\n",
      "Train Epoch: 124 [20480/50000 (45%)]\tLoss: 0.016349, Accuracy: 99.61\n",
      "Train Epoch: 124 [21760/50000 (48%)]\tLoss: 0.062722, Accuracy: 97.66\n",
      "Train Epoch: 124 [23040/50000 (51%)]\tLoss: 0.067686, Accuracy: 98.05\n",
      "Train Epoch: 124 [24320/50000 (54%)]\tLoss: 0.011990, Accuracy: 99.22\n",
      "Train Epoch: 124 [25600/50000 (57%)]\tLoss: 0.027223, Accuracy: 98.83\n",
      "Train Epoch: 124 [26880/50000 (60%)]\tLoss: 0.025779, Accuracy: 99.22\n",
      "Train Epoch: 124 [28160/50000 (62%)]\tLoss: 0.009921, Accuracy: 100.00\n",
      "Train Epoch: 124 [29440/50000 (65%)]\tLoss: 0.065840, Accuracy: 97.27\n",
      "Train Epoch: 124 [30720/50000 (68%)]\tLoss: 0.089055, Accuracy: 98.05\n",
      "Train Epoch: 124 [32000/50000 (71%)]\tLoss: 0.010962, Accuracy: 100.00\n",
      "Train Epoch: 124 [33280/50000 (74%)]\tLoss: 0.067389, Accuracy: 97.66\n",
      "Train Epoch: 124 [34560/50000 (77%)]\tLoss: 0.023436, Accuracy: 98.83\n",
      "Train Epoch: 124 [35840/50000 (80%)]\tLoss: 0.058066, Accuracy: 98.05\n",
      "Train Epoch: 124 [37120/50000 (82%)]\tLoss: 0.011953, Accuracy: 99.61\n",
      "Train Epoch: 124 [38400/50000 (85%)]\tLoss: 0.029554, Accuracy: 98.83\n",
      "Train Epoch: 124 [39680/50000 (88%)]\tLoss: 0.014392, Accuracy: 99.61\n",
      "Train Epoch: 124 [40960/50000 (91%)]\tLoss: 0.023099, Accuracy: 99.61\n",
      "Train Epoch: 124 [42240/50000 (94%)]\tLoss: 0.020531, Accuracy: 99.22\n",
      "Train Epoch: 124 [43520/50000 (97%)]\tLoss: 0.021677, Accuracy: 99.22\n",
      "Train Epoch: 124 [35000/50000 (99%)]\tLoss: 0.010544, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5728, Accuracy: 4465/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.344400882720947 s]\n",
      "Train Epoch: 125 [0/50000 (0%)]\tLoss: 0.018284, Accuracy: 99.22\n",
      "Train Epoch: 125 [1280/50000 (3%)]\tLoss: 0.061228, Accuracy: 98.83\n",
      "Train Epoch: 125 [2560/50000 (6%)]\tLoss: 0.028116, Accuracy: 98.44\n",
      "Train Epoch: 125 [3840/50000 (9%)]\tLoss: 0.006921, Accuracy: 100.00\n",
      "Train Epoch: 125 [5120/50000 (11%)]\tLoss: 0.013977, Accuracy: 99.61\n",
      "Train Epoch: 125 [6400/50000 (14%)]\tLoss: 0.015388, Accuracy: 99.61\n",
      "Train Epoch: 125 [7680/50000 (17%)]\tLoss: 0.017391, Accuracy: 99.61\n",
      "Train Epoch: 125 [8960/50000 (20%)]\tLoss: 0.044467, Accuracy: 98.05\n",
      "Train Epoch: 125 [10240/50000 (23%)]\tLoss: 0.040988, Accuracy: 99.22\n",
      "Train Epoch: 125 [11520/50000 (26%)]\tLoss: 0.003900, Accuracy: 100.00\n",
      "Train Epoch: 125 [12800/50000 (28%)]\tLoss: 0.058180, Accuracy: 98.05\n",
      "Train Epoch: 125 [14080/50000 (31%)]\tLoss: 0.009946, Accuracy: 99.61\n",
      "Train Epoch: 125 [15360/50000 (34%)]\tLoss: 0.024177, Accuracy: 99.22\n",
      "Train Epoch: 125 [16640/50000 (37%)]\tLoss: 0.017143, Accuracy: 99.61\n",
      "Train Epoch: 125 [17920/50000 (40%)]\tLoss: 0.018920, Accuracy: 99.22\n",
      "Train Epoch: 125 [19200/50000 (43%)]\tLoss: 0.006129, Accuracy: 100.00\n",
      "Train Epoch: 125 [20480/50000 (45%)]\tLoss: 0.009855, Accuracy: 99.61\n",
      "Train Epoch: 125 [21760/50000 (48%)]\tLoss: 0.014822, Accuracy: 99.22\n",
      "Train Epoch: 125 [23040/50000 (51%)]\tLoss: 0.019476, Accuracy: 99.22\n",
      "Train Epoch: 125 [24320/50000 (54%)]\tLoss: 0.029364, Accuracy: 98.05\n",
      "Train Epoch: 125 [25600/50000 (57%)]\tLoss: 0.016805, Accuracy: 99.22\n",
      "Train Epoch: 125 [26880/50000 (60%)]\tLoss: 0.017452, Accuracy: 99.61\n",
      "Train Epoch: 125 [28160/50000 (62%)]\tLoss: 0.051021, Accuracy: 98.44\n",
      "Train Epoch: 125 [29440/50000 (65%)]\tLoss: 0.021065, Accuracy: 99.61\n",
      "Train Epoch: 125 [30720/50000 (68%)]\tLoss: 0.035729, Accuracy: 98.83\n",
      "Train Epoch: 125 [32000/50000 (71%)]\tLoss: 0.013498, Accuracy: 98.83\n",
      "Train Epoch: 125 [33280/50000 (74%)]\tLoss: 0.046690, Accuracy: 98.44\n",
      "Train Epoch: 125 [34560/50000 (77%)]\tLoss: 0.013668, Accuracy: 99.61\n",
      "Train Epoch: 125 [35840/50000 (80%)]\tLoss: 0.009436, Accuracy: 99.61\n",
      "Train Epoch: 125 [37120/50000 (82%)]\tLoss: 0.037561, Accuracy: 98.83\n",
      "Train Epoch: 125 [38400/50000 (85%)]\tLoss: 0.020839, Accuracy: 99.22\n",
      "Train Epoch: 125 [39680/50000 (88%)]\tLoss: 0.008653, Accuracy: 99.61\n",
      "Train Epoch: 125 [40960/50000 (91%)]\tLoss: 0.005536, Accuracy: 100.00\n",
      "Train Epoch: 125 [42240/50000 (94%)]\tLoss: 0.029428, Accuracy: 99.22\n",
      "Train Epoch: 125 [43520/50000 (97%)]\tLoss: 0.072109, Accuracy: 96.88\n",
      "Train Epoch: 125 [35000/50000 (99%)]\tLoss: 0.038748, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5702, Accuracy: 4473/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.38569974899292 s]\n",
      "Train Epoch: 126 [0/50000 (0%)]\tLoss: 0.035216, Accuracy: 98.83\n",
      "Train Epoch: 126 [1280/50000 (3%)]\tLoss: 0.018131, Accuracy: 99.61\n",
      "Train Epoch: 126 [2560/50000 (6%)]\tLoss: 0.010059, Accuracy: 99.61\n",
      "Train Epoch: 126 [3840/50000 (9%)]\tLoss: 0.024250, Accuracy: 99.22\n",
      "Train Epoch: 126 [5120/50000 (11%)]\tLoss: 0.034161, Accuracy: 98.44\n",
      "Train Epoch: 126 [6400/50000 (14%)]\tLoss: 0.054385, Accuracy: 98.44\n",
      "Train Epoch: 126 [7680/50000 (17%)]\tLoss: 0.050549, Accuracy: 98.05\n",
      "Train Epoch: 126 [8960/50000 (20%)]\tLoss: 0.008897, Accuracy: 99.61\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 126 [10240/50000 (23%)]\tLoss: 0.042234, Accuracy: 98.44\n",
      "Train Epoch: 126 [11520/50000 (26%)]\tLoss: 0.024670, Accuracy: 98.83\n",
      "Train Epoch: 126 [12800/50000 (28%)]\tLoss: 0.008797, Accuracy: 99.61\n",
      "Train Epoch: 126 [14080/50000 (31%)]\tLoss: 0.019833, Accuracy: 99.61\n",
      "Train Epoch: 126 [15360/50000 (34%)]\tLoss: 0.020841, Accuracy: 99.22\n",
      "Train Epoch: 126 [16640/50000 (37%)]\tLoss: 0.024457, Accuracy: 98.44\n",
      "Train Epoch: 126 [17920/50000 (40%)]\tLoss: 0.008157, Accuracy: 99.61\n",
      "Train Epoch: 126 [19200/50000 (43%)]\tLoss: 0.012441, Accuracy: 100.00\n",
      "Train Epoch: 126 [20480/50000 (45%)]\tLoss: 0.019797, Accuracy: 99.61\n",
      "Train Epoch: 126 [21760/50000 (48%)]\tLoss: 0.037444, Accuracy: 98.83\n",
      "Train Epoch: 126 [23040/50000 (51%)]\tLoss: 0.019562, Accuracy: 99.61\n",
      "Train Epoch: 126 [24320/50000 (54%)]\tLoss: 0.019241, Accuracy: 98.83\n",
      "Train Epoch: 126 [25600/50000 (57%)]\tLoss: 0.032406, Accuracy: 98.44\n",
      "Train Epoch: 126 [26880/50000 (60%)]\tLoss: 0.009076, Accuracy: 100.00\n",
      "Train Epoch: 126 [28160/50000 (62%)]\tLoss: 0.016853, Accuracy: 99.22\n",
      "Train Epoch: 126 [29440/50000 (65%)]\tLoss: 0.019192, Accuracy: 98.83\n",
      "Train Epoch: 126 [30720/50000 (68%)]\tLoss: 0.009476, Accuracy: 99.61\n",
      "Train Epoch: 126 [32000/50000 (71%)]\tLoss: 0.025463, Accuracy: 99.61\n",
      "Train Epoch: 126 [33280/50000 (74%)]\tLoss: 0.013381, Accuracy: 99.61\n",
      "Train Epoch: 126 [34560/50000 (77%)]\tLoss: 0.044362, Accuracy: 98.83\n",
      "Train Epoch: 126 [35840/50000 (80%)]\tLoss: 0.035234, Accuracy: 98.44\n",
      "Train Epoch: 126 [37120/50000 (82%)]\tLoss: 0.028074, Accuracy: 98.44\n",
      "Train Epoch: 126 [38400/50000 (85%)]\tLoss: 0.009218, Accuracy: 100.00\n",
      "Train Epoch: 126 [39680/50000 (88%)]\tLoss: 0.024382, Accuracy: 99.22\n",
      "Train Epoch: 126 [40960/50000 (91%)]\tLoss: 0.013469, Accuracy: 99.61\n",
      "Train Epoch: 126 [42240/50000 (94%)]\tLoss: 0.021573, Accuracy: 98.83\n",
      "Train Epoch: 126 [43520/50000 (97%)]\tLoss: 0.008629, Accuracy: 99.61\n",
      "Train Epoch: 126 [35000/50000 (99%)]\tLoss: 0.024054, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5613, Accuracy: 4474/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.373315572738647 s]\n",
      "Train Epoch: 127 [0/50000 (0%)]\tLoss: 0.006186, Accuracy: 100.00\n",
      "Train Epoch: 127 [1280/50000 (3%)]\tLoss: 0.011525, Accuracy: 99.22\n",
      "Train Epoch: 127 [2560/50000 (6%)]\tLoss: 0.015103, Accuracy: 99.61\n",
      "Train Epoch: 127 [3840/50000 (9%)]\tLoss: 0.036396, Accuracy: 98.83\n",
      "Train Epoch: 127 [5120/50000 (11%)]\tLoss: 0.024307, Accuracy: 98.83\n",
      "Train Epoch: 127 [6400/50000 (14%)]\tLoss: 0.015189, Accuracy: 98.83\n",
      "Train Epoch: 127 [7680/50000 (17%)]\tLoss: 0.014750, Accuracy: 99.22\n",
      "Train Epoch: 127 [8960/50000 (20%)]\tLoss: 0.041721, Accuracy: 98.44\n",
      "Train Epoch: 127 [10240/50000 (23%)]\tLoss: 0.017141, Accuracy: 99.61\n",
      "Train Epoch: 127 [11520/50000 (26%)]\tLoss: 0.016705, Accuracy: 99.22\n",
      "Train Epoch: 127 [12800/50000 (28%)]\tLoss: 0.016819, Accuracy: 99.22\n",
      "Train Epoch: 127 [14080/50000 (31%)]\tLoss: 0.033341, Accuracy: 98.44\n",
      "Train Epoch: 127 [15360/50000 (34%)]\tLoss: 0.020923, Accuracy: 98.83\n",
      "Train Epoch: 127 [16640/50000 (37%)]\tLoss: 0.013436, Accuracy: 99.61\n",
      "Train Epoch: 127 [17920/50000 (40%)]\tLoss: 0.031932, Accuracy: 98.44\n",
      "Train Epoch: 127 [19200/50000 (43%)]\tLoss: 0.024360, Accuracy: 98.83\n",
      "Train Epoch: 127 [20480/50000 (45%)]\tLoss: 0.016678, Accuracy: 99.22\n",
      "Train Epoch: 127 [21760/50000 (48%)]\tLoss: 0.015411, Accuracy: 99.61\n",
      "Train Epoch: 127 [23040/50000 (51%)]\tLoss: 0.025394, Accuracy: 99.22\n",
      "Train Epoch: 127 [24320/50000 (54%)]\tLoss: 0.021247, Accuracy: 99.22\n",
      "Train Epoch: 127 [25600/50000 (57%)]\tLoss: 0.048909, Accuracy: 98.44\n",
      "Train Epoch: 127 [26880/50000 (60%)]\tLoss: 0.017251, Accuracy: 99.22\n",
      "Train Epoch: 127 [28160/50000 (62%)]\tLoss: 0.026799, Accuracy: 98.83\n",
      "Train Epoch: 127 [29440/50000 (65%)]\tLoss: 0.052084, Accuracy: 98.05\n",
      "Train Epoch: 127 [30720/50000 (68%)]\tLoss: 0.012328, Accuracy: 99.61\n",
      "Train Epoch: 127 [32000/50000 (71%)]\tLoss: 0.006629, Accuracy: 100.00\n",
      "Train Epoch: 127 [33280/50000 (74%)]\tLoss: 0.036262, Accuracy: 99.22\n",
      "Train Epoch: 127 [34560/50000 (77%)]\tLoss: 0.029784, Accuracy: 98.83\n",
      "Train Epoch: 127 [35840/50000 (80%)]\tLoss: 0.030387, Accuracy: 98.83\n",
      "Train Epoch: 127 [37120/50000 (82%)]\tLoss: 0.010145, Accuracy: 100.00\n",
      "Train Epoch: 127 [38400/50000 (85%)]\tLoss: 0.007172, Accuracy: 100.00\n",
      "Train Epoch: 127 [39680/50000 (88%)]\tLoss: 0.011538, Accuracy: 99.61\n",
      "Train Epoch: 127 [40960/50000 (91%)]\tLoss: 0.011992, Accuracy: 99.61\n",
      "Train Epoch: 127 [42240/50000 (94%)]\tLoss: 0.028267, Accuracy: 98.83\n",
      "Train Epoch: 127 [43520/50000 (97%)]\tLoss: 0.012316, Accuracy: 99.61\n",
      "Train Epoch: 127 [35000/50000 (99%)]\tLoss: 0.019701, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5644, Accuracy: 4474/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.370653867721558 s]\n",
      "Train Epoch: 128 [0/50000 (0%)]\tLoss: 0.008022, Accuracy: 100.00\n",
      "Train Epoch: 128 [1280/50000 (3%)]\tLoss: 0.029609, Accuracy: 99.61\n",
      "Train Epoch: 128 [2560/50000 (6%)]\tLoss: 0.030580, Accuracy: 98.44\n",
      "Train Epoch: 128 [3840/50000 (9%)]\tLoss: 0.033657, Accuracy: 98.44\n",
      "Train Epoch: 128 [5120/50000 (11%)]\tLoss: 0.017224, Accuracy: 99.61\n",
      "Train Epoch: 128 [6400/50000 (14%)]\tLoss: 0.033135, Accuracy: 98.83\n",
      "Train Epoch: 128 [7680/50000 (17%)]\tLoss: 0.035323, Accuracy: 98.05\n",
      "Train Epoch: 128 [8960/50000 (20%)]\tLoss: 0.080566, Accuracy: 96.88\n",
      "Train Epoch: 128 [10240/50000 (23%)]\tLoss: 0.015830, Accuracy: 99.22\n",
      "Train Epoch: 128 [11520/50000 (26%)]\tLoss: 0.037751, Accuracy: 98.44\n",
      "Train Epoch: 128 [12800/50000 (28%)]\tLoss: 0.019208, Accuracy: 99.22\n",
      "Train Epoch: 128 [14080/50000 (31%)]\tLoss: 0.007575, Accuracy: 100.00\n",
      "Train Epoch: 128 [15360/50000 (34%)]\tLoss: 0.010634, Accuracy: 100.00\n",
      "Train Epoch: 128 [16640/50000 (37%)]\tLoss: 0.012639, Accuracy: 99.61\n",
      "Train Epoch: 128 [17920/50000 (40%)]\tLoss: 0.054463, Accuracy: 96.88\n",
      "Train Epoch: 128 [19200/50000 (43%)]\tLoss: 0.038081, Accuracy: 99.22\n",
      "Train Epoch: 128 [20480/50000 (45%)]\tLoss: 0.017565, Accuracy: 99.22\n",
      "Train Epoch: 128 [21760/50000 (48%)]\tLoss: 0.012170, Accuracy: 100.00\n",
      "Train Epoch: 128 [23040/50000 (51%)]\tLoss: 0.008725, Accuracy: 99.61\n",
      "Train Epoch: 128 [24320/50000 (54%)]\tLoss: 0.014136, Accuracy: 99.61\n",
      "Train Epoch: 128 [25600/50000 (57%)]\tLoss: 0.069942, Accuracy: 96.88\n",
      "Train Epoch: 128 [26880/50000 (60%)]\tLoss: 0.029787, Accuracy: 98.83\n",
      "Train Epoch: 128 [28160/50000 (62%)]\tLoss: 0.008734, Accuracy: 100.00\n",
      "Train Epoch: 128 [29440/50000 (65%)]\tLoss: 0.010380, Accuracy: 100.00\n",
      "Train Epoch: 128 [30720/50000 (68%)]\tLoss: 0.027431, Accuracy: 99.22\n",
      "Train Epoch: 128 [32000/50000 (71%)]\tLoss: 0.014801, Accuracy: 99.61\n",
      "Train Epoch: 128 [33280/50000 (74%)]\tLoss: 0.027719, Accuracy: 99.22\n",
      "Train Epoch: 128 [34560/50000 (77%)]\tLoss: 0.017406, Accuracy: 99.61\n",
      "Train Epoch: 128 [35840/50000 (80%)]\tLoss: 0.012694, Accuracy: 100.00\n",
      "Train Epoch: 128 [37120/50000 (82%)]\tLoss: 0.026949, Accuracy: 99.22\n",
      "Train Epoch: 128 [38400/50000 (85%)]\tLoss: 0.044396, Accuracy: 98.44\n",
      "Train Epoch: 128 [39680/50000 (88%)]\tLoss: 0.023897, Accuracy: 99.22\n",
      "Train Epoch: 128 [40960/50000 (91%)]\tLoss: 0.023875, Accuracy: 98.83\n",
      "Train Epoch: 128 [42240/50000 (94%)]\tLoss: 0.006615, Accuracy: 99.61\n",
      "Train Epoch: 128 [43520/50000 (97%)]\tLoss: 0.014092, Accuracy: 99.22\n",
      "Train Epoch: 128 [35000/50000 (99%)]\tLoss: 0.033747, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5874, Accuracy: 4466/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.53590226173401 s]\n",
      "Train Epoch: 129 [0/50000 (0%)]\tLoss: 0.024442, Accuracy: 99.22\n",
      "Train Epoch: 129 [1280/50000 (3%)]\tLoss: 0.016101, Accuracy: 99.61\n",
      "Train Epoch: 129 [2560/50000 (6%)]\tLoss: 0.007267, Accuracy: 99.61\n",
      "Train Epoch: 129 [3840/50000 (9%)]\tLoss: 0.025731, Accuracy: 98.44\n",
      "Train Epoch: 129 [5120/50000 (11%)]\tLoss: 0.006372, Accuracy: 100.00\n",
      "Train Epoch: 129 [6400/50000 (14%)]\tLoss: 0.032033, Accuracy: 98.83\n",
      "Train Epoch: 129 [7680/50000 (17%)]\tLoss: 0.014843, Accuracy: 99.61\n",
      "Train Epoch: 129 [8960/50000 (20%)]\tLoss: 0.020416, Accuracy: 99.61\n",
      "Train Epoch: 129 [10240/50000 (23%)]\tLoss: 0.027331, Accuracy: 98.83\n",
      "Train Epoch: 129 [11520/50000 (26%)]\tLoss: 0.018415, Accuracy: 99.22\n",
      "Train Epoch: 129 [12800/50000 (28%)]\tLoss: 0.031732, Accuracy: 98.44\n",
      "Train Epoch: 129 [14080/50000 (31%)]\tLoss: 0.049676, Accuracy: 98.83\n",
      "Train Epoch: 129 [15360/50000 (34%)]\tLoss: 0.024147, Accuracy: 98.83\n",
      "Train Epoch: 129 [16640/50000 (37%)]\tLoss: 0.043685, Accuracy: 98.83\n",
      "Train Epoch: 129 [17920/50000 (40%)]\tLoss: 0.006545, Accuracy: 100.00\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 129 [19200/50000 (43%)]\tLoss: 0.011360, Accuracy: 100.00\n",
      "Train Epoch: 129 [20480/50000 (45%)]\tLoss: 0.052864, Accuracy: 98.05\n",
      "Train Epoch: 129 [21760/50000 (48%)]\tLoss: 0.029444, Accuracy: 99.22\n",
      "Train Epoch: 129 [23040/50000 (51%)]\tLoss: 0.038645, Accuracy: 98.44\n",
      "Train Epoch: 129 [24320/50000 (54%)]\tLoss: 0.029619, Accuracy: 98.83\n",
      "Train Epoch: 129 [25600/50000 (57%)]\tLoss: 0.042886, Accuracy: 98.83\n",
      "Train Epoch: 129 [26880/50000 (60%)]\tLoss: 0.043182, Accuracy: 98.05\n",
      "Train Epoch: 129 [28160/50000 (62%)]\tLoss: 0.016899, Accuracy: 99.22\n",
      "Train Epoch: 129 [29440/50000 (65%)]\tLoss: 0.023653, Accuracy: 98.83\n",
      "Train Epoch: 129 [30720/50000 (68%)]\tLoss: 0.018880, Accuracy: 99.22\n",
      "Train Epoch: 129 [32000/50000 (71%)]\tLoss: 0.083600, Accuracy: 97.66\n",
      "Train Epoch: 129 [33280/50000 (74%)]\tLoss: 0.008968, Accuracy: 99.61\n",
      "Train Epoch: 129 [34560/50000 (77%)]\tLoss: 0.027124, Accuracy: 98.83\n",
      "Train Epoch: 129 [35840/50000 (80%)]\tLoss: 0.031208, Accuracy: 98.44\n",
      "Train Epoch: 129 [37120/50000 (82%)]\tLoss: 0.016455, Accuracy: 99.22\n",
      "Train Epoch: 129 [38400/50000 (85%)]\tLoss: 0.016076, Accuracy: 99.61\n",
      "Train Epoch: 129 [39680/50000 (88%)]\tLoss: 0.019540, Accuracy: 99.22\n",
      "Train Epoch: 129 [40960/50000 (91%)]\tLoss: 0.035373, Accuracy: 98.44\n",
      "Train Epoch: 129 [42240/50000 (94%)]\tLoss: 0.021462, Accuracy: 99.61\n",
      "Train Epoch: 129 [43520/50000 (97%)]\tLoss: 0.037507, Accuracy: 98.83\n",
      "Train Epoch: 129 [35000/50000 (99%)]\tLoss: 0.041629, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5687, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.352271556854248 s]\n",
      "Train Epoch: 130 [0/50000 (0%)]\tLoss: 0.046133, Accuracy: 99.22\n",
      "Train Epoch: 130 [1280/50000 (3%)]\tLoss: 0.006290, Accuracy: 99.61\n",
      "Train Epoch: 130 [2560/50000 (6%)]\tLoss: 0.026121, Accuracy: 98.83\n",
      "Train Epoch: 130 [3840/50000 (9%)]\tLoss: 0.037085, Accuracy: 98.44\n",
      "Train Epoch: 130 [5120/50000 (11%)]\tLoss: 0.028413, Accuracy: 98.83\n",
      "Train Epoch: 130 [6400/50000 (14%)]\tLoss: 0.024451, Accuracy: 98.83\n",
      "Train Epoch: 130 [7680/50000 (17%)]\tLoss: 0.023223, Accuracy: 98.83\n",
      "Train Epoch: 130 [8960/50000 (20%)]\tLoss: 0.013204, Accuracy: 99.61\n",
      "Train Epoch: 130 [10240/50000 (23%)]\tLoss: 0.002891, Accuracy: 100.00\n",
      "Train Epoch: 130 [11520/50000 (26%)]\tLoss: 0.019020, Accuracy: 99.61\n",
      "Train Epoch: 130 [12800/50000 (28%)]\tLoss: 0.011918, Accuracy: 99.61\n",
      "Train Epoch: 130 [14080/50000 (31%)]\tLoss: 0.016742, Accuracy: 99.61\n",
      "Train Epoch: 130 [15360/50000 (34%)]\tLoss: 0.007661, Accuracy: 99.61\n",
      "Train Epoch: 130 [16640/50000 (37%)]\tLoss: 0.019850, Accuracy: 99.22\n",
      "Train Epoch: 130 [17920/50000 (40%)]\tLoss: 0.013918, Accuracy: 99.22\n",
      "Train Epoch: 130 [19200/50000 (43%)]\tLoss: 0.024183, Accuracy: 99.22\n",
      "Train Epoch: 130 [20480/50000 (45%)]\tLoss: 0.032185, Accuracy: 98.05\n",
      "Train Epoch: 130 [21760/50000 (48%)]\tLoss: 0.010987, Accuracy: 100.00\n",
      "Train Epoch: 130 [23040/50000 (51%)]\tLoss: 0.013453, Accuracy: 99.22\n",
      "Train Epoch: 130 [24320/50000 (54%)]\tLoss: 0.020311, Accuracy: 99.22\n",
      "Train Epoch: 130 [25600/50000 (57%)]\tLoss: 0.031644, Accuracy: 98.44\n",
      "Train Epoch: 130 [26880/50000 (60%)]\tLoss: 0.018893, Accuracy: 99.22\n",
      "Train Epoch: 130 [28160/50000 (62%)]\tLoss: 0.028813, Accuracy: 99.61\n",
      "Train Epoch: 130 [29440/50000 (65%)]\tLoss: 0.017656, Accuracy: 99.61\n",
      "Train Epoch: 130 [30720/50000 (68%)]\tLoss: 0.008752, Accuracy: 99.61\n",
      "Train Epoch: 130 [32000/50000 (71%)]\tLoss: 0.025918, Accuracy: 98.83\n",
      "Train Epoch: 130 [33280/50000 (74%)]\tLoss: 0.015039, Accuracy: 99.61\n",
      "Train Epoch: 130 [34560/50000 (77%)]\tLoss: 0.026094, Accuracy: 98.44\n",
      "Train Epoch: 130 [35840/50000 (80%)]\tLoss: 0.022699, Accuracy: 99.22\n",
      "Train Epoch: 130 [37120/50000 (82%)]\tLoss: 0.029599, Accuracy: 99.22\n",
      "Train Epoch: 130 [38400/50000 (85%)]\tLoss: 0.011071, Accuracy: 99.61\n",
      "Train Epoch: 130 [39680/50000 (88%)]\tLoss: 0.032690, Accuracy: 98.83\n",
      "Train Epoch: 130 [40960/50000 (91%)]\tLoss: 0.024251, Accuracy: 98.83\n",
      "Train Epoch: 130 [42240/50000 (94%)]\tLoss: 0.021800, Accuracy: 98.83\n",
      "Train Epoch: 130 [43520/50000 (97%)]\tLoss: 0.033120, Accuracy: 98.44\n",
      "Train Epoch: 130 [35000/50000 (99%)]\tLoss: 0.060584, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5789, Accuracy: 4462/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.345600128173828 s]\n",
      "Train Epoch: 131 [0/50000 (0%)]\tLoss: 0.014677, Accuracy: 99.61\n",
      "Train Epoch: 131 [1280/50000 (3%)]\tLoss: 0.014669, Accuracy: 99.61\n",
      "Train Epoch: 131 [2560/50000 (6%)]\tLoss: 0.027121, Accuracy: 98.44\n",
      "Train Epoch: 131 [3840/50000 (9%)]\tLoss: 0.047354, Accuracy: 98.44\n",
      "Train Epoch: 131 [5120/50000 (11%)]\tLoss: 0.041854, Accuracy: 98.05\n",
      "Train Epoch: 131 [6400/50000 (14%)]\tLoss: 0.008426, Accuracy: 99.61\n",
      "Train Epoch: 131 [7680/50000 (17%)]\tLoss: 0.015761, Accuracy: 99.61\n",
      "Train Epoch: 131 [8960/50000 (20%)]\tLoss: 0.012369, Accuracy: 99.61\n",
      "Train Epoch: 131 [10240/50000 (23%)]\tLoss: 0.017028, Accuracy: 99.22\n",
      "Train Epoch: 131 [11520/50000 (26%)]\tLoss: 0.045108, Accuracy: 98.44\n",
      "Train Epoch: 131 [12800/50000 (28%)]\tLoss: 0.008758, Accuracy: 100.00\n",
      "Train Epoch: 131 [14080/50000 (31%)]\tLoss: 0.016043, Accuracy: 99.61\n",
      "Train Epoch: 131 [15360/50000 (34%)]\tLoss: 0.052686, Accuracy: 98.83\n",
      "Train Epoch: 131 [16640/50000 (37%)]\tLoss: 0.032351, Accuracy: 99.22\n",
      "Train Epoch: 131 [17920/50000 (40%)]\tLoss: 0.019441, Accuracy: 99.22\n",
      "Train Epoch: 131 [19200/50000 (43%)]\tLoss: 0.027699, Accuracy: 99.22\n",
      "Train Epoch: 131 [20480/50000 (45%)]\tLoss: 0.029383, Accuracy: 99.22\n",
      "Train Epoch: 131 [21760/50000 (48%)]\tLoss: 0.030982, Accuracy: 98.44\n",
      "Train Epoch: 131 [23040/50000 (51%)]\tLoss: 0.022716, Accuracy: 99.22\n",
      "Train Epoch: 131 [24320/50000 (54%)]\tLoss: 0.016702, Accuracy: 99.22\n",
      "Train Epoch: 131 [25600/50000 (57%)]\tLoss: 0.008981, Accuracy: 100.00\n",
      "Train Epoch: 131 [26880/50000 (60%)]\tLoss: 0.054413, Accuracy: 96.88\n",
      "Train Epoch: 131 [28160/50000 (62%)]\tLoss: 0.030908, Accuracy: 98.83\n",
      "Train Epoch: 131 [29440/50000 (65%)]\tLoss: 0.042164, Accuracy: 98.44\n",
      "Train Epoch: 131 [30720/50000 (68%)]\tLoss: 0.031532, Accuracy: 98.44\n",
      "Train Epoch: 131 [32000/50000 (71%)]\tLoss: 0.008632, Accuracy: 100.00\n",
      "Train Epoch: 131 [33280/50000 (74%)]\tLoss: 0.021153, Accuracy: 99.22\n",
      "Train Epoch: 131 [34560/50000 (77%)]\tLoss: 0.013101, Accuracy: 99.61\n",
      "Train Epoch: 131 [35840/50000 (80%)]\tLoss: 0.041233, Accuracy: 98.83\n",
      "Train Epoch: 131 [37120/50000 (82%)]\tLoss: 0.020128, Accuracy: 99.22\n",
      "Train Epoch: 131 [38400/50000 (85%)]\tLoss: 0.020243, Accuracy: 99.22\n",
      "Train Epoch: 131 [39680/50000 (88%)]\tLoss: 0.038013, Accuracy: 98.05\n",
      "Train Epoch: 131 [40960/50000 (91%)]\tLoss: 0.046475, Accuracy: 98.83\n",
      "Train Epoch: 131 [42240/50000 (94%)]\tLoss: 0.024443, Accuracy: 99.22\n",
      "Train Epoch: 131 [43520/50000 (97%)]\tLoss: 0.019512, Accuracy: 98.83\n",
      "Train Epoch: 131 [35000/50000 (99%)]\tLoss: 0.020944, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5628, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.357104301452637 s]\n",
      "Train Epoch: 132 [0/50000 (0%)]\tLoss: 0.005311, Accuracy: 100.00\n",
      "Train Epoch: 132 [1280/50000 (3%)]\tLoss: 0.023095, Accuracy: 98.44\n",
      "Train Epoch: 132 [2560/50000 (6%)]\tLoss: 0.043192, Accuracy: 98.83\n",
      "Train Epoch: 132 [3840/50000 (9%)]\tLoss: 0.016477, Accuracy: 99.22\n",
      "Train Epoch: 132 [5120/50000 (11%)]\tLoss: 0.014284, Accuracy: 98.83\n",
      "Train Epoch: 132 [6400/50000 (14%)]\tLoss: 0.016812, Accuracy: 99.61\n",
      "Train Epoch: 132 [7680/50000 (17%)]\tLoss: 0.010221, Accuracy: 99.22\n",
      "Train Epoch: 132 [8960/50000 (20%)]\tLoss: 0.011215, Accuracy: 99.61\n",
      "Train Epoch: 132 [10240/50000 (23%)]\tLoss: 0.066386, Accuracy: 98.05\n",
      "Train Epoch: 132 [11520/50000 (26%)]\tLoss: 0.025999, Accuracy: 98.44\n",
      "Train Epoch: 132 [12800/50000 (28%)]\tLoss: 0.025763, Accuracy: 98.83\n",
      "Train Epoch: 132 [14080/50000 (31%)]\tLoss: 0.019034, Accuracy: 99.22\n",
      "Train Epoch: 132 [15360/50000 (34%)]\tLoss: 0.041504, Accuracy: 98.44\n",
      "Train Epoch: 132 [16640/50000 (37%)]\tLoss: 0.009939, Accuracy: 99.61\n",
      "Train Epoch: 132 [17920/50000 (40%)]\tLoss: 0.007568, Accuracy: 99.61\n",
      "Train Epoch: 132 [19200/50000 (43%)]\tLoss: 0.030120, Accuracy: 99.22\n",
      "Train Epoch: 132 [20480/50000 (45%)]\tLoss: 0.004699, Accuracy: 99.61\n",
      "Train Epoch: 132 [21760/50000 (48%)]\tLoss: 0.068577, Accuracy: 97.66\n",
      "Train Epoch: 132 [23040/50000 (51%)]\tLoss: 0.030422, Accuracy: 98.83\n",
      "Train Epoch: 132 [24320/50000 (54%)]\tLoss: 0.011452, Accuracy: 99.61\n",
      "Train Epoch: 132 [25600/50000 (57%)]\tLoss: 0.004126, Accuracy: 100.00\n",
      "Train Epoch: 132 [26880/50000 (60%)]\tLoss: 0.025218, Accuracy: 99.61\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 132 [28160/50000 (62%)]\tLoss: 0.030267, Accuracy: 98.83\n",
      "Train Epoch: 132 [29440/50000 (65%)]\tLoss: 0.007986, Accuracy: 100.00\n",
      "Train Epoch: 132 [30720/50000 (68%)]\tLoss: 0.008540, Accuracy: 99.61\n",
      "Train Epoch: 132 [32000/50000 (71%)]\tLoss: 0.016349, Accuracy: 99.61\n",
      "Train Epoch: 132 [33280/50000 (74%)]\tLoss: 0.025263, Accuracy: 98.44\n",
      "Train Epoch: 132 [34560/50000 (77%)]\tLoss: 0.034172, Accuracy: 99.22\n",
      "Train Epoch: 132 [35840/50000 (80%)]\tLoss: 0.036064, Accuracy: 98.44\n",
      "Train Epoch: 132 [37120/50000 (82%)]\tLoss: 0.024873, Accuracy: 98.44\n",
      "Train Epoch: 132 [38400/50000 (85%)]\tLoss: 0.019291, Accuracy: 99.61\n",
      "Train Epoch: 132 [39680/50000 (88%)]\tLoss: 0.012122, Accuracy: 99.22\n",
      "Train Epoch: 132 [40960/50000 (91%)]\tLoss: 0.020004, Accuracy: 99.22\n",
      "Train Epoch: 132 [42240/50000 (94%)]\tLoss: 0.014641, Accuracy: 99.22\n",
      "Train Epoch: 132 [43520/50000 (97%)]\tLoss: 0.016060, Accuracy: 99.22\n",
      "Train Epoch: 132 [35000/50000 (99%)]\tLoss: 0.008041, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5626, Accuracy: 4475/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.338979721069336 s]\n",
      "Train Epoch: 133 [0/50000 (0%)]\tLoss: 0.015431, Accuracy: 99.22\n",
      "Train Epoch: 133 [1280/50000 (3%)]\tLoss: 0.033965, Accuracy: 98.83\n",
      "Train Epoch: 133 [2560/50000 (6%)]\tLoss: 0.032956, Accuracy: 98.44\n",
      "Train Epoch: 133 [3840/50000 (9%)]\tLoss: 0.047496, Accuracy: 98.83\n",
      "Train Epoch: 133 [5120/50000 (11%)]\tLoss: 0.016025, Accuracy: 99.61\n",
      "Train Epoch: 133 [6400/50000 (14%)]\tLoss: 0.039829, Accuracy: 99.22\n",
      "Train Epoch: 133 [7680/50000 (17%)]\tLoss: 0.020547, Accuracy: 99.61\n",
      "Train Epoch: 133 [8960/50000 (20%)]\tLoss: 0.028742, Accuracy: 99.22\n",
      "Train Epoch: 133 [10240/50000 (23%)]\tLoss: 0.012717, Accuracy: 100.00\n",
      "Train Epoch: 133 [11520/50000 (26%)]\tLoss: 0.021663, Accuracy: 99.61\n",
      "Train Epoch: 133 [12800/50000 (28%)]\tLoss: 0.012499, Accuracy: 99.61\n",
      "Train Epoch: 133 [14080/50000 (31%)]\tLoss: 0.013284, Accuracy: 99.22\n",
      "Train Epoch: 133 [15360/50000 (34%)]\tLoss: 0.033603, Accuracy: 98.44\n",
      "Train Epoch: 133 [16640/50000 (37%)]\tLoss: 0.007030, Accuracy: 99.61\n",
      "Train Epoch: 133 [17920/50000 (40%)]\tLoss: 0.017754, Accuracy: 99.22\n",
      "Train Epoch: 133 [19200/50000 (43%)]\tLoss: 0.040049, Accuracy: 98.44\n",
      "Train Epoch: 133 [20480/50000 (45%)]\tLoss: 0.014703, Accuracy: 99.61\n",
      "Train Epoch: 133 [21760/50000 (48%)]\tLoss: 0.039633, Accuracy: 98.05\n",
      "Train Epoch: 133 [23040/50000 (51%)]\tLoss: 0.020447, Accuracy: 98.83\n",
      "Train Epoch: 133 [24320/50000 (54%)]\tLoss: 0.012087, Accuracy: 99.61\n",
      "Train Epoch: 133 [25600/50000 (57%)]\tLoss: 0.020348, Accuracy: 99.22\n",
      "Train Epoch: 133 [26880/50000 (60%)]\tLoss: 0.022993, Accuracy: 98.83\n",
      "Train Epoch: 133 [28160/50000 (62%)]\tLoss: 0.030812, Accuracy: 98.83\n",
      "Train Epoch: 133 [29440/50000 (65%)]\tLoss: 0.080565, Accuracy: 97.66\n",
      "Train Epoch: 133 [30720/50000 (68%)]\tLoss: 0.037004, Accuracy: 98.83\n",
      "Train Epoch: 133 [32000/50000 (71%)]\tLoss: 0.034046, Accuracy: 98.83\n",
      "Train Epoch: 133 [33280/50000 (74%)]\tLoss: 0.029413, Accuracy: 99.22\n",
      "Train Epoch: 133 [34560/50000 (77%)]\tLoss: 0.009728, Accuracy: 99.61\n",
      "Train Epoch: 133 [35840/50000 (80%)]\tLoss: 0.012049, Accuracy: 99.61\n",
      "Train Epoch: 133 [37120/50000 (82%)]\tLoss: 0.024676, Accuracy: 99.22\n",
      "Train Epoch: 133 [38400/50000 (85%)]\tLoss: 0.035212, Accuracy: 98.83\n",
      "Train Epoch: 133 [39680/50000 (88%)]\tLoss: 0.021793, Accuracy: 98.83\n",
      "Train Epoch: 133 [40960/50000 (91%)]\tLoss: 0.029118, Accuracy: 99.22\n",
      "Train Epoch: 133 [42240/50000 (94%)]\tLoss: 0.009938, Accuracy: 99.61\n",
      "Train Epoch: 133 [43520/50000 (97%)]\tLoss: 0.041228, Accuracy: 99.22\n",
      "Train Epoch: 133 [35000/50000 (99%)]\tLoss: 0.069892, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.5726, Accuracy: 4466/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.348848342895508 s]\n",
      "Train Epoch: 134 [0/50000 (0%)]\tLoss: 0.023547, Accuracy: 98.44\n",
      "Train Epoch: 134 [1280/50000 (3%)]\tLoss: 0.045888, Accuracy: 99.22\n",
      "Train Epoch: 134 [2560/50000 (6%)]\tLoss: 0.021303, Accuracy: 99.61\n",
      "Train Epoch: 134 [3840/50000 (9%)]\tLoss: 0.016527, Accuracy: 99.61\n",
      "Train Epoch: 134 [5120/50000 (11%)]\tLoss: 0.024133, Accuracy: 99.22\n",
      "Train Epoch: 134 [6400/50000 (14%)]\tLoss: 0.038729, Accuracy: 98.05\n",
      "Train Epoch: 134 [7680/50000 (17%)]\tLoss: 0.023781, Accuracy: 99.22\n",
      "Train Epoch: 134 [8960/50000 (20%)]\tLoss: 0.017653, Accuracy: 99.61\n",
      "Train Epoch: 134 [10240/50000 (23%)]\tLoss: 0.013774, Accuracy: 99.22\n",
      "Train Epoch: 134 [11520/50000 (26%)]\tLoss: 0.032464, Accuracy: 98.83\n",
      "Train Epoch: 134 [12800/50000 (28%)]\tLoss: 0.018326, Accuracy: 99.61\n",
      "Train Epoch: 134 [14080/50000 (31%)]\tLoss: 0.055028, Accuracy: 98.44\n",
      "Train Epoch: 134 [15360/50000 (34%)]\tLoss: 0.013142, Accuracy: 100.00\n",
      "Train Epoch: 134 [16640/50000 (37%)]\tLoss: 0.014920, Accuracy: 99.61\n",
      "Train Epoch: 134 [17920/50000 (40%)]\tLoss: 0.011360, Accuracy: 99.22\n",
      "Train Epoch: 134 [19200/50000 (43%)]\tLoss: 0.016332, Accuracy: 99.22\n",
      "Train Epoch: 134 [20480/50000 (45%)]\tLoss: 0.021208, Accuracy: 99.22\n",
      "Train Epoch: 134 [21760/50000 (48%)]\tLoss: 0.019096, Accuracy: 99.22\n",
      "Train Epoch: 134 [23040/50000 (51%)]\tLoss: 0.032413, Accuracy: 98.83\n",
      "Train Epoch: 134 [24320/50000 (54%)]\tLoss: 0.014081, Accuracy: 99.22\n",
      "Train Epoch: 134 [25600/50000 (57%)]\tLoss: 0.030360, Accuracy: 99.22\n",
      "Train Epoch: 134 [26880/50000 (60%)]\tLoss: 0.053841, Accuracy: 98.05\n",
      "Train Epoch: 134 [28160/50000 (62%)]\tLoss: 0.003934, Accuracy: 100.00\n",
      "Train Epoch: 134 [29440/50000 (65%)]\tLoss: 0.037724, Accuracy: 98.44\n",
      "Train Epoch: 134 [30720/50000 (68%)]\tLoss: 0.016671, Accuracy: 98.83\n",
      "Train Epoch: 134 [32000/50000 (71%)]\tLoss: 0.029519, Accuracy: 98.83\n",
      "Train Epoch: 134 [33280/50000 (74%)]\tLoss: 0.022461, Accuracy: 98.83\n",
      "Train Epoch: 134 [34560/50000 (77%)]\tLoss: 0.030268, Accuracy: 98.44\n",
      "Train Epoch: 134 [35840/50000 (80%)]\tLoss: 0.030890, Accuracy: 98.83\n",
      "Train Epoch: 134 [37120/50000 (82%)]\tLoss: 0.029281, Accuracy: 98.83\n",
      "Train Epoch: 134 [38400/50000 (85%)]\tLoss: 0.015660, Accuracy: 99.22\n",
      "Train Epoch: 134 [39680/50000 (88%)]\tLoss: 0.021541, Accuracy: 99.22\n",
      "Train Epoch: 134 [40960/50000 (91%)]\tLoss: 0.061027, Accuracy: 98.44\n",
      "Train Epoch: 134 [42240/50000 (94%)]\tLoss: 0.008931, Accuracy: 99.61\n",
      "Train Epoch: 134 [43520/50000 (97%)]\tLoss: 0.017020, Accuracy: 99.22\n",
      "Train Epoch: 134 [35000/50000 (99%)]\tLoss: 0.023650, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5681, Accuracy: 4465/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.33921527862549 s]\n",
      "Train Epoch: 135 [0/50000 (0%)]\tLoss: 0.005040, Accuracy: 100.00\n",
      "Train Epoch: 135 [1280/50000 (3%)]\tLoss: 0.014616, Accuracy: 99.61\n",
      "Train Epoch: 135 [2560/50000 (6%)]\tLoss: 0.033828, Accuracy: 98.44\n",
      "Train Epoch: 135 [3840/50000 (9%)]\tLoss: 0.021490, Accuracy: 99.22\n",
      "Train Epoch: 135 [5120/50000 (11%)]\tLoss: 0.007178, Accuracy: 100.00\n",
      "Train Epoch: 135 [6400/50000 (14%)]\tLoss: 0.035297, Accuracy: 99.22\n",
      "Train Epoch: 135 [7680/50000 (17%)]\tLoss: 0.019664, Accuracy: 98.83\n",
      "Train Epoch: 135 [8960/50000 (20%)]\tLoss: 0.010735, Accuracy: 100.00\n",
      "Train Epoch: 135 [10240/50000 (23%)]\tLoss: 0.021699, Accuracy: 99.22\n",
      "Train Epoch: 135 [11520/50000 (26%)]\tLoss: 0.018953, Accuracy: 99.22\n",
      "Train Epoch: 135 [12800/50000 (28%)]\tLoss: 0.047392, Accuracy: 98.83\n",
      "Train Epoch: 135 [14080/50000 (31%)]\tLoss: 0.034281, Accuracy: 99.22\n",
      "Train Epoch: 135 [15360/50000 (34%)]\tLoss: 0.009783, Accuracy: 100.00\n",
      "Train Epoch: 135 [16640/50000 (37%)]\tLoss: 0.016390, Accuracy: 99.22\n",
      "Train Epoch: 135 [17920/50000 (40%)]\tLoss: 0.039094, Accuracy: 98.83\n",
      "Train Epoch: 135 [19200/50000 (43%)]\tLoss: 0.017222, Accuracy: 99.61\n",
      "Train Epoch: 135 [20480/50000 (45%)]\tLoss: 0.029071, Accuracy: 99.22\n",
      "Train Epoch: 135 [21760/50000 (48%)]\tLoss: 0.019333, Accuracy: 99.22\n",
      "Train Epoch: 135 [23040/50000 (51%)]\tLoss: 0.019112, Accuracy: 99.22\n",
      "Train Epoch: 135 [24320/50000 (54%)]\tLoss: 0.020849, Accuracy: 99.22\n",
      "Train Epoch: 135 [25600/50000 (57%)]\tLoss: 0.032000, Accuracy: 99.22\n",
      "Train Epoch: 135 [26880/50000 (60%)]\tLoss: 0.034050, Accuracy: 98.83\n",
      "Train Epoch: 135 [28160/50000 (62%)]\tLoss: 0.021599, Accuracy: 98.83\n",
      "Train Epoch: 135 [29440/50000 (65%)]\tLoss: 0.027924, Accuracy: 98.44\n",
      "Train Epoch: 135 [30720/50000 (68%)]\tLoss: 0.019856, Accuracy: 99.61\n",
      "Train Epoch: 135 [32000/50000 (71%)]\tLoss: 0.025760, Accuracy: 98.83\n",
      "Train Epoch: 135 [33280/50000 (74%)]\tLoss: 0.024021, Accuracy: 98.44\n",
      "Train Epoch: 135 [34560/50000 (77%)]\tLoss: 0.051784, Accuracy: 98.05\n",
      "Train Epoch: 135 [35840/50000 (80%)]\tLoss: 0.066577, Accuracy: 97.27\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 135 [37120/50000 (82%)]\tLoss: 0.011214, Accuracy: 99.61\n",
      "Train Epoch: 135 [38400/50000 (85%)]\tLoss: 0.013693, Accuracy: 99.22\n",
      "Train Epoch: 135 [39680/50000 (88%)]\tLoss: 0.016246, Accuracy: 99.61\n",
      "Train Epoch: 135 [40960/50000 (91%)]\tLoss: 0.067063, Accuracy: 96.88\n",
      "Train Epoch: 135 [42240/50000 (94%)]\tLoss: 0.025893, Accuracy: 98.83\n",
      "Train Epoch: 135 [43520/50000 (97%)]\tLoss: 0.034944, Accuracy: 99.22\n",
      "Train Epoch: 135 [35000/50000 (99%)]\tLoss: 0.013952, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5665, Accuracy: 4476/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.303750038146973 s]\n",
      "Train Epoch: 136 [0/50000 (0%)]\tLoss: 0.028604, Accuracy: 98.83\n",
      "Train Epoch: 136 [1280/50000 (3%)]\tLoss: 0.020503, Accuracy: 99.22\n",
      "Train Epoch: 136 [2560/50000 (6%)]\tLoss: 0.006177, Accuracy: 100.00\n",
      "Train Epoch: 136 [3840/50000 (9%)]\tLoss: 0.031373, Accuracy: 99.22\n",
      "Train Epoch: 136 [5120/50000 (11%)]\tLoss: 0.021522, Accuracy: 99.61\n",
      "Train Epoch: 136 [6400/50000 (14%)]\tLoss: 0.008256, Accuracy: 99.61\n",
      "Train Epoch: 136 [7680/50000 (17%)]\tLoss: 0.020241, Accuracy: 99.61\n",
      "Train Epoch: 136 [8960/50000 (20%)]\tLoss: 0.009174, Accuracy: 99.61\n",
      "Train Epoch: 136 [10240/50000 (23%)]\tLoss: 0.067418, Accuracy: 98.44\n",
      "Train Epoch: 136 [11520/50000 (26%)]\tLoss: 0.007517, Accuracy: 99.61\n",
      "Train Epoch: 136 [12800/50000 (28%)]\tLoss: 0.039690, Accuracy: 98.44\n",
      "Train Epoch: 136 [14080/50000 (31%)]\tLoss: 0.006888, Accuracy: 100.00\n",
      "Train Epoch: 136 [15360/50000 (34%)]\tLoss: 0.021594, Accuracy: 98.83\n",
      "Train Epoch: 136 [16640/50000 (37%)]\tLoss: 0.056541, Accuracy: 98.44\n",
      "Train Epoch: 136 [17920/50000 (40%)]\tLoss: 0.018773, Accuracy: 99.22\n",
      "Train Epoch: 136 [19200/50000 (43%)]\tLoss: 0.054859, Accuracy: 98.05\n",
      "Train Epoch: 136 [20480/50000 (45%)]\tLoss: 0.009374, Accuracy: 99.61\n",
      "Train Epoch: 136 [21760/50000 (48%)]\tLoss: 0.053675, Accuracy: 98.44\n",
      "Train Epoch: 136 [23040/50000 (51%)]\tLoss: 0.029477, Accuracy: 98.83\n",
      "Train Epoch: 136 [24320/50000 (54%)]\tLoss: 0.018624, Accuracy: 98.83\n",
      "Train Epoch: 136 [25600/50000 (57%)]\tLoss: 0.029205, Accuracy: 98.83\n",
      "Train Epoch: 136 [26880/50000 (60%)]\tLoss: 0.061255, Accuracy: 97.66\n",
      "Train Epoch: 136 [28160/50000 (62%)]\tLoss: 0.010315, Accuracy: 99.61\n",
      "Train Epoch: 136 [29440/50000 (65%)]\tLoss: 0.004019, Accuracy: 100.00\n",
      "Train Epoch: 136 [30720/50000 (68%)]\tLoss: 0.024463, Accuracy: 99.22\n",
      "Train Epoch: 136 [32000/50000 (71%)]\tLoss: 0.015780, Accuracy: 99.22\n",
      "Train Epoch: 136 [33280/50000 (74%)]\tLoss: 0.015701, Accuracy: 99.61\n",
      "Train Epoch: 136 [34560/50000 (77%)]\tLoss: 0.042970, Accuracy: 98.05\n",
      "Train Epoch: 136 [35840/50000 (80%)]\tLoss: 0.022096, Accuracy: 99.22\n",
      "Train Epoch: 136 [37120/50000 (82%)]\tLoss: 0.004524, Accuracy: 100.00\n",
      "Train Epoch: 136 [38400/50000 (85%)]\tLoss: 0.028959, Accuracy: 98.44\n",
      "Train Epoch: 136 [39680/50000 (88%)]\tLoss: 0.017379, Accuracy: 99.61\n",
      "Train Epoch: 136 [40960/50000 (91%)]\tLoss: 0.012233, Accuracy: 99.61\n",
      "Train Epoch: 136 [42240/50000 (94%)]\tLoss: 0.046456, Accuracy: 98.44\n",
      "Train Epoch: 136 [43520/50000 (97%)]\tLoss: 0.015783, Accuracy: 99.22\n",
      "Train Epoch: 136 [35000/50000 (99%)]\tLoss: 0.013962, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5646, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.305665493011475 s]\n",
      "Train Epoch: 137 [0/50000 (0%)]\tLoss: 0.004441, Accuracy: 100.00\n",
      "Train Epoch: 137 [1280/50000 (3%)]\tLoss: 0.066760, Accuracy: 97.27\n",
      "Train Epoch: 137 [2560/50000 (6%)]\tLoss: 0.028822, Accuracy: 99.22\n",
      "Train Epoch: 137 [3840/50000 (9%)]\tLoss: 0.007897, Accuracy: 100.00\n",
      "Train Epoch: 137 [5120/50000 (11%)]\tLoss: 0.016240, Accuracy: 99.61\n",
      "Train Epoch: 137 [6400/50000 (14%)]\tLoss: 0.015826, Accuracy: 99.22\n",
      "Train Epoch: 137 [7680/50000 (17%)]\tLoss: 0.046411, Accuracy: 98.05\n",
      "Train Epoch: 137 [8960/50000 (20%)]\tLoss: 0.031607, Accuracy: 97.66\n",
      "Train Epoch: 137 [10240/50000 (23%)]\tLoss: 0.007797, Accuracy: 99.61\n",
      "Train Epoch: 137 [11520/50000 (26%)]\tLoss: 0.031059, Accuracy: 99.22\n",
      "Train Epoch: 137 [12800/50000 (28%)]\tLoss: 0.021608, Accuracy: 98.83\n",
      "Train Epoch: 137 [14080/50000 (31%)]\tLoss: 0.006735, Accuracy: 100.00\n",
      "Train Epoch: 137 [15360/50000 (34%)]\tLoss: 0.028943, Accuracy: 98.83\n",
      "Train Epoch: 137 [16640/50000 (37%)]\tLoss: 0.034140, Accuracy: 98.83\n",
      "Train Epoch: 137 [17920/50000 (40%)]\tLoss: 0.016717, Accuracy: 99.61\n",
      "Train Epoch: 137 [19200/50000 (43%)]\tLoss: 0.031994, Accuracy: 98.83\n",
      "Train Epoch: 137 [20480/50000 (45%)]\tLoss: 0.011725, Accuracy: 99.61\n",
      "Train Epoch: 137 [21760/50000 (48%)]\tLoss: 0.030748, Accuracy: 99.22\n",
      "Train Epoch: 137 [23040/50000 (51%)]\tLoss: 0.024315, Accuracy: 98.83\n",
      "Train Epoch: 137 [24320/50000 (54%)]\tLoss: 0.034288, Accuracy: 98.83\n",
      "Train Epoch: 137 [25600/50000 (57%)]\tLoss: 0.027572, Accuracy: 99.22\n",
      "Train Epoch: 137 [26880/50000 (60%)]\tLoss: 0.028147, Accuracy: 98.44\n",
      "Train Epoch: 137 [28160/50000 (62%)]\tLoss: 0.015151, Accuracy: 99.61\n",
      "Train Epoch: 137 [29440/50000 (65%)]\tLoss: 0.007656, Accuracy: 100.00\n",
      "Train Epoch: 137 [30720/50000 (68%)]\tLoss: 0.007861, Accuracy: 99.61\n",
      "Train Epoch: 137 [32000/50000 (71%)]\tLoss: 0.012254, Accuracy: 100.00\n",
      "Train Epoch: 137 [33280/50000 (74%)]\tLoss: 0.004438, Accuracy: 100.00\n",
      "Train Epoch: 137 [34560/50000 (77%)]\tLoss: 0.016804, Accuracy: 99.22\n",
      "Train Epoch: 137 [35840/50000 (80%)]\tLoss: 0.063038, Accuracy: 97.66\n",
      "Train Epoch: 137 [37120/50000 (82%)]\tLoss: 0.027801, Accuracy: 99.22\n",
      "Train Epoch: 137 [38400/50000 (85%)]\tLoss: 0.044688, Accuracy: 98.83\n",
      "Train Epoch: 137 [39680/50000 (88%)]\tLoss: 0.007244, Accuracy: 100.00\n",
      "Train Epoch: 137 [40960/50000 (91%)]\tLoss: 0.004280, Accuracy: 100.00\n",
      "Train Epoch: 137 [42240/50000 (94%)]\tLoss: 0.022193, Accuracy: 99.22\n",
      "Train Epoch: 137 [43520/50000 (97%)]\tLoss: 0.037892, Accuracy: 99.22\n",
      "Train Epoch: 137 [35000/50000 (99%)]\tLoss: 0.035258, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5687, Accuracy: 4477/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.34417223930359 s]\n",
      "Train Epoch: 138 [0/50000 (0%)]\tLoss: 0.020006, Accuracy: 99.61\n",
      "Train Epoch: 138 [1280/50000 (3%)]\tLoss: 0.044082, Accuracy: 98.05\n",
      "Train Epoch: 138 [2560/50000 (6%)]\tLoss: 0.008661, Accuracy: 100.00\n",
      "Train Epoch: 138 [3840/50000 (9%)]\tLoss: 0.026104, Accuracy: 99.61\n",
      "Train Epoch: 138 [5120/50000 (11%)]\tLoss: 0.026980, Accuracy: 98.83\n",
      "Train Epoch: 138 [6400/50000 (14%)]\tLoss: 0.013435, Accuracy: 99.61\n",
      "Train Epoch: 138 [7680/50000 (17%)]\tLoss: 0.004366, Accuracy: 100.00\n",
      "Train Epoch: 138 [8960/50000 (20%)]\tLoss: 0.011072, Accuracy: 99.61\n",
      "Train Epoch: 138 [10240/50000 (23%)]\tLoss: 0.015181, Accuracy: 99.22\n",
      "Train Epoch: 138 [11520/50000 (26%)]\tLoss: 0.013163, Accuracy: 99.61\n",
      "Train Epoch: 138 [12800/50000 (28%)]\tLoss: 0.036554, Accuracy: 98.44\n",
      "Train Epoch: 138 [14080/50000 (31%)]\tLoss: 0.017791, Accuracy: 99.22\n",
      "Train Epoch: 138 [15360/50000 (34%)]\tLoss: 0.008584, Accuracy: 100.00\n",
      "Train Epoch: 138 [16640/50000 (37%)]\tLoss: 0.019799, Accuracy: 98.83\n",
      "Train Epoch: 138 [17920/50000 (40%)]\tLoss: 0.016483, Accuracy: 99.22\n",
      "Train Epoch: 138 [19200/50000 (43%)]\tLoss: 0.021080, Accuracy: 99.61\n",
      "Train Epoch: 138 [20480/50000 (45%)]\tLoss: 0.051037, Accuracy: 98.05\n",
      "Train Epoch: 138 [21760/50000 (48%)]\tLoss: 0.046542, Accuracy: 98.05\n",
      "Train Epoch: 138 [23040/50000 (51%)]\tLoss: 0.024212, Accuracy: 99.22\n",
      "Train Epoch: 138 [24320/50000 (54%)]\tLoss: 0.028344, Accuracy: 98.44\n",
      "Train Epoch: 138 [25600/50000 (57%)]\tLoss: 0.010974, Accuracy: 100.00\n",
      "Train Epoch: 138 [26880/50000 (60%)]\tLoss: 0.004526, Accuracy: 100.00\n",
      "Train Epoch: 138 [28160/50000 (62%)]\tLoss: 0.032893, Accuracy: 99.22\n",
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      "Train Epoch: 138 [30720/50000 (68%)]\tLoss: 0.014021, Accuracy: 99.61\n",
      "Train Epoch: 138 [32000/50000 (71%)]\tLoss: 0.027520, Accuracy: 99.22\n",
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      "Train Epoch: 138 [34560/50000 (77%)]\tLoss: 0.018845, Accuracy: 99.22\n",
      "Train Epoch: 138 [35840/50000 (80%)]\tLoss: 0.026770, Accuracy: 98.44\n",
      "Train Epoch: 138 [37120/50000 (82%)]\tLoss: 0.026585, Accuracy: 99.22\n",
      "Train Epoch: 138 [38400/50000 (85%)]\tLoss: 0.016076, Accuracy: 99.22\n",
      "Train Epoch: 138 [39680/50000 (88%)]\tLoss: 0.052897, Accuracy: 98.44\n",
      "Train Epoch: 138 [40960/50000 (91%)]\tLoss: 0.026133, Accuracy: 99.22\n",
      "Train Epoch: 138 [42240/50000 (94%)]\tLoss: 0.014310, Accuracy: 99.61\n",
      "Train Epoch: 138 [43520/50000 (97%)]\tLoss: 0.002429, Accuracy: 100.00\n",
      "Train Epoch: 138 [35000/50000 (99%)]\tLoss: 0.016991, Accuracy: 99.50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Validation set: Average loss: 0.5695, Accuracy: 4468/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.375481605529785 s]\n",
      "Train Epoch: 139 [0/50000 (0%)]\tLoss: 0.028809, Accuracy: 98.83\n",
      "Train Epoch: 139 [1280/50000 (3%)]\tLoss: 0.009386, Accuracy: 100.00\n",
      "Train Epoch: 139 [2560/50000 (6%)]\tLoss: 0.019787, Accuracy: 99.22\n",
      "Train Epoch: 139 [3840/50000 (9%)]\tLoss: 0.032244, Accuracy: 98.44\n",
      "Train Epoch: 139 [5120/50000 (11%)]\tLoss: 0.009156, Accuracy: 99.61\n",
      "Train Epoch: 139 [6400/50000 (14%)]\tLoss: 0.017421, Accuracy: 99.61\n",
      "Train Epoch: 139 [7680/50000 (17%)]\tLoss: 0.022565, Accuracy: 99.22\n",
      "Train Epoch: 139 [8960/50000 (20%)]\tLoss: 0.006151, Accuracy: 100.00\n",
      "Train Epoch: 139 [10240/50000 (23%)]\tLoss: 0.024377, Accuracy: 98.44\n",
      "Train Epoch: 139 [11520/50000 (26%)]\tLoss: 0.017545, Accuracy: 99.22\n",
      "Train Epoch: 139 [12800/50000 (28%)]\tLoss: 0.009919, Accuracy: 99.22\n",
      "Train Epoch: 139 [14080/50000 (31%)]\tLoss: 0.021291, Accuracy: 98.83\n",
      "Train Epoch: 139 [15360/50000 (34%)]\tLoss: 0.030286, Accuracy: 99.22\n",
      "Train Epoch: 139 [16640/50000 (37%)]\tLoss: 0.054463, Accuracy: 98.44\n",
      "Train Epoch: 139 [17920/50000 (40%)]\tLoss: 0.028467, Accuracy: 99.22\n",
      "Train Epoch: 139 [19200/50000 (43%)]\tLoss: 0.018898, Accuracy: 99.22\n",
      "Train Epoch: 139 [20480/50000 (45%)]\tLoss: 0.009238, Accuracy: 100.00\n",
      "Train Epoch: 139 [21760/50000 (48%)]\tLoss: 0.010818, Accuracy: 99.61\n",
      "Train Epoch: 139 [23040/50000 (51%)]\tLoss: 0.008221, Accuracy: 100.00\n",
      "Train Epoch: 139 [24320/50000 (54%)]\tLoss: 0.010515, Accuracy: 99.61\n",
      "Train Epoch: 139 [25600/50000 (57%)]\tLoss: 0.042253, Accuracy: 98.44\n",
      "Train Epoch: 139 [26880/50000 (60%)]\tLoss: 0.035460, Accuracy: 99.22\n",
      "Train Epoch: 139 [28160/50000 (62%)]\tLoss: 0.029502, Accuracy: 98.83\n",
      "Train Epoch: 139 [29440/50000 (65%)]\tLoss: 0.026009, Accuracy: 99.22\n",
      "Train Epoch: 139 [30720/50000 (68%)]\tLoss: 0.024457, Accuracy: 99.22\n",
      "Train Epoch: 139 [32000/50000 (71%)]\tLoss: 0.049747, Accuracy: 98.44\n",
      "Train Epoch: 139 [33280/50000 (74%)]\tLoss: 0.009357, Accuracy: 100.00\n",
      "Train Epoch: 139 [34560/50000 (77%)]\tLoss: 0.014105, Accuracy: 99.22\n",
      "Train Epoch: 139 [35840/50000 (80%)]\tLoss: 0.031636, Accuracy: 98.83\n",
      "Train Epoch: 139 [37120/50000 (82%)]\tLoss: 0.031437, Accuracy: 98.44\n",
      "Train Epoch: 139 [38400/50000 (85%)]\tLoss: 0.019483, Accuracy: 99.22\n",
      "Train Epoch: 139 [39680/50000 (88%)]\tLoss: 0.007897, Accuracy: 100.00\n",
      "Train Epoch: 139 [40960/50000 (91%)]\tLoss: 0.015246, Accuracy: 99.22\n",
      "Train Epoch: 139 [42240/50000 (94%)]\tLoss: 0.022211, Accuracy: 98.83\n",
      "Train Epoch: 139 [43520/50000 (97%)]\tLoss: 0.021689, Accuracy: 98.83\n",
      "Train Epoch: 139 [35000/50000 (99%)]\tLoss: 0.027683, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5864, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.387092351913452 s]\n",
      "Train Epoch: 140 [0/50000 (0%)]\tLoss: 0.033164, Accuracy: 98.83\n",
      "Train Epoch: 140 [1280/50000 (3%)]\tLoss: 0.008147, Accuracy: 100.00\n",
      "Train Epoch: 140 [2560/50000 (6%)]\tLoss: 0.016502, Accuracy: 99.61\n",
      "Train Epoch: 140 [3840/50000 (9%)]\tLoss: 0.053365, Accuracy: 98.05\n",
      "Train Epoch: 140 [5120/50000 (11%)]\tLoss: 0.023558, Accuracy: 99.22\n",
      "Train Epoch: 140 [6400/50000 (14%)]\tLoss: 0.012793, Accuracy: 99.61\n",
      "Train Epoch: 140 [7680/50000 (17%)]\tLoss: 0.009895, Accuracy: 99.61\n",
      "Train Epoch: 140 [8960/50000 (20%)]\tLoss: 0.022582, Accuracy: 98.83\n",
      "Train Epoch: 140 [10240/50000 (23%)]\tLoss: 0.019984, Accuracy: 99.22\n",
      "Train Epoch: 140 [11520/50000 (26%)]\tLoss: 0.010620, Accuracy: 99.22\n",
      "Train Epoch: 140 [12800/50000 (28%)]\tLoss: 0.021075, Accuracy: 99.22\n",
      "Train Epoch: 140 [14080/50000 (31%)]\tLoss: 0.010360, Accuracy: 99.61\n",
      "Train Epoch: 140 [15360/50000 (34%)]\tLoss: 0.021659, Accuracy: 99.22\n",
      "Train Epoch: 140 [16640/50000 (37%)]\tLoss: 0.025382, Accuracy: 98.83\n",
      "Train Epoch: 140 [17920/50000 (40%)]\tLoss: 0.021423, Accuracy: 98.83\n",
      "Train Epoch: 140 [19200/50000 (43%)]\tLoss: 0.013091, Accuracy: 99.61\n",
      "Train Epoch: 140 [20480/50000 (45%)]\tLoss: 0.040633, Accuracy: 98.05\n",
      "Train Epoch: 140 [21760/50000 (48%)]\tLoss: 0.007750, Accuracy: 100.00\n",
      "Train Epoch: 140 [23040/50000 (51%)]\tLoss: 0.028050, Accuracy: 98.05\n",
      "Train Epoch: 140 [24320/50000 (54%)]\tLoss: 0.048314, Accuracy: 98.83\n",
      "Train Epoch: 140 [25600/50000 (57%)]\tLoss: 0.013101, Accuracy: 100.00\n",
      "Train Epoch: 140 [26880/50000 (60%)]\tLoss: 0.017348, Accuracy: 99.61\n",
      "Train Epoch: 140 [28160/50000 (62%)]\tLoss: 0.018010, Accuracy: 99.22\n",
      "Train Epoch: 140 [29440/50000 (65%)]\tLoss: 0.008398, Accuracy: 100.00\n",
      "Train Epoch: 140 [30720/50000 (68%)]\tLoss: 0.029634, Accuracy: 98.83\n",
      "Train Epoch: 140 [32000/50000 (71%)]\tLoss: 0.011826, Accuracy: 99.61\n",
      "Train Epoch: 140 [33280/50000 (74%)]\tLoss: 0.010761, Accuracy: 99.61\n",
      "Train Epoch: 140 [34560/50000 (77%)]\tLoss: 0.007595, Accuracy: 100.00\n",
      "Train Epoch: 140 [35840/50000 (80%)]\tLoss: 0.021880, Accuracy: 99.61\n",
      "Train Epoch: 140 [37120/50000 (82%)]\tLoss: 0.025855, Accuracy: 98.83\n",
      "Train Epoch: 140 [38400/50000 (85%)]\tLoss: 0.021725, Accuracy: 99.61\n",
      "Train Epoch: 140 [39680/50000 (88%)]\tLoss: 0.012728, Accuracy: 100.00\n",
      "Train Epoch: 140 [40960/50000 (91%)]\tLoss: 0.075485, Accuracy: 97.66\n",
      "Train Epoch: 140 [42240/50000 (94%)]\tLoss: 0.013835, Accuracy: 99.22\n",
      "Train Epoch: 140 [43520/50000 (97%)]\tLoss: 0.050762, Accuracy: 98.44\n",
      "Train Epoch: 140 [35000/50000 (99%)]\tLoss: 0.023699, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5677, Accuracy: 4471/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.29751706123352 s]\n",
      "Train Epoch: 141 [0/50000 (0%)]\tLoss: 0.047603, Accuracy: 98.05\n",
      "Train Epoch: 141 [1280/50000 (3%)]\tLoss: 0.019059, Accuracy: 99.61\n",
      "Train Epoch: 141 [2560/50000 (6%)]\tLoss: 0.030038, Accuracy: 98.05\n",
      "Train Epoch: 141 [3840/50000 (9%)]\tLoss: 0.023912, Accuracy: 99.22\n",
      "Train Epoch: 141 [5120/50000 (11%)]\tLoss: 0.047646, Accuracy: 98.44\n",
      "Train Epoch: 141 [6400/50000 (14%)]\tLoss: 0.029897, Accuracy: 97.66\n",
      "Train Epoch: 141 [7680/50000 (17%)]\tLoss: 0.023241, Accuracy: 98.83\n",
      "Train Epoch: 141 [8960/50000 (20%)]\tLoss: 0.050172, Accuracy: 98.05\n",
      "Train Epoch: 141 [10240/50000 (23%)]\tLoss: 0.025429, Accuracy: 98.83\n",
      "Train Epoch: 141 [11520/50000 (26%)]\tLoss: 0.013375, Accuracy: 99.61\n",
      "Train Epoch: 141 [12800/50000 (28%)]\tLoss: 0.039783, Accuracy: 98.83\n",
      "Train Epoch: 141 [14080/50000 (31%)]\tLoss: 0.035481, Accuracy: 99.22\n",
      "Train Epoch: 141 [15360/50000 (34%)]\tLoss: 0.007625, Accuracy: 100.00\n",
      "Train Epoch: 141 [16640/50000 (37%)]\tLoss: 0.048093, Accuracy: 98.44\n",
      "Train Epoch: 141 [17920/50000 (40%)]\tLoss: 0.015412, Accuracy: 99.22\n",
      "Train Epoch: 141 [19200/50000 (43%)]\tLoss: 0.007132, Accuracy: 99.61\n",
      "Train Epoch: 141 [20480/50000 (45%)]\tLoss: 0.028433, Accuracy: 98.83\n",
      "Train Epoch: 141 [21760/50000 (48%)]\tLoss: 0.012955, Accuracy: 99.61\n",
      "Train Epoch: 141 [23040/50000 (51%)]\tLoss: 0.011802, Accuracy: 99.61\n",
      "Train Epoch: 141 [24320/50000 (54%)]\tLoss: 0.024186, Accuracy: 99.61\n",
      "Train Epoch: 141 [25600/50000 (57%)]\tLoss: 0.022156, Accuracy: 99.22\n",
      "Train Epoch: 141 [26880/50000 (60%)]\tLoss: 0.021613, Accuracy: 99.22\n",
      "Train Epoch: 141 [28160/50000 (62%)]\tLoss: 0.014102, Accuracy: 99.61\n",
      "Train Epoch: 141 [29440/50000 (65%)]\tLoss: 0.018956, Accuracy: 99.22\n",
      "Train Epoch: 141 [30720/50000 (68%)]\tLoss: 0.010148, Accuracy: 100.00\n",
      "Train Epoch: 141 [32000/50000 (71%)]\tLoss: 0.035918, Accuracy: 99.22\n",
      "Train Epoch: 141 [33280/50000 (74%)]\tLoss: 0.012644, Accuracy: 99.61\n",
      "Train Epoch: 141 [34560/50000 (77%)]\tLoss: 0.017592, Accuracy: 99.22\n",
      "Train Epoch: 141 [35840/50000 (80%)]\tLoss: 0.027272, Accuracy: 98.44\n",
      "Train Epoch: 141 [37120/50000 (82%)]\tLoss: 0.024941, Accuracy: 98.83\n",
      "Train Epoch: 141 [38400/50000 (85%)]\tLoss: 0.018039, Accuracy: 99.22\n",
      "Train Epoch: 141 [39680/50000 (88%)]\tLoss: 0.025233, Accuracy: 98.83\n",
      "Train Epoch: 141 [40960/50000 (91%)]\tLoss: 0.028267, Accuracy: 98.83\n",
      "Train Epoch: 141 [42240/50000 (94%)]\tLoss: 0.015573, Accuracy: 99.61\n",
      "Train Epoch: 141 [43520/50000 (97%)]\tLoss: 0.014409, Accuracy: 99.61\n",
      "Train Epoch: 141 [35000/50000 (99%)]\tLoss: 0.032708, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5685, Accuracy: 4470/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.3011417388916 s]\n",
      "Train Epoch: 142 [0/50000 (0%)]\tLoss: 0.013777, Accuracy: 99.61\n",
      "Train Epoch: 142 [1280/50000 (3%)]\tLoss: 0.031914, Accuracy: 99.22\n",
      "Train Epoch: 142 [2560/50000 (6%)]\tLoss: 0.046866, Accuracy: 98.05\n",
      "Train Epoch: 142 [3840/50000 (9%)]\tLoss: 0.040923, Accuracy: 98.44\n",
      "Train Epoch: 142 [5120/50000 (11%)]\tLoss: 0.031068, Accuracy: 98.83\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 142 [6400/50000 (14%)]\tLoss: 0.015852, Accuracy: 99.61\n",
      "Train Epoch: 142 [7680/50000 (17%)]\tLoss: 0.008096, Accuracy: 100.00\n",
      "Train Epoch: 142 [8960/50000 (20%)]\tLoss: 0.008856, Accuracy: 100.00\n",
      "Train Epoch: 142 [10240/50000 (23%)]\tLoss: 0.025793, Accuracy: 98.83\n",
      "Train Epoch: 142 [11520/50000 (26%)]\tLoss: 0.016038, Accuracy: 99.61\n",
      "Train Epoch: 142 [12800/50000 (28%)]\tLoss: 0.053006, Accuracy: 98.83\n",
      "Train Epoch: 142 [14080/50000 (31%)]\tLoss: 0.010085, Accuracy: 99.61\n",
      "Train Epoch: 142 [15360/50000 (34%)]\tLoss: 0.020684, Accuracy: 98.83\n",
      "Train Epoch: 142 [16640/50000 (37%)]\tLoss: 0.018452, Accuracy: 98.44\n",
      "Train Epoch: 142 [17920/50000 (40%)]\tLoss: 0.028289, Accuracy: 99.22\n",
      "Train Epoch: 142 [19200/50000 (43%)]\tLoss: 0.006587, Accuracy: 100.00\n",
      "Train Epoch: 142 [20480/50000 (45%)]\tLoss: 0.014985, Accuracy: 99.61\n",
      "Train Epoch: 142 [21760/50000 (48%)]\tLoss: 0.020437, Accuracy: 98.83\n",
      "Train Epoch: 142 [23040/50000 (51%)]\tLoss: 0.025229, Accuracy: 98.83\n",
      "Train Epoch: 142 [24320/50000 (54%)]\tLoss: 0.053530, Accuracy: 98.83\n",
      "Train Epoch: 142 [25600/50000 (57%)]\tLoss: 0.019940, Accuracy: 99.61\n",
      "Train Epoch: 142 [26880/50000 (60%)]\tLoss: 0.018005, Accuracy: 99.61\n",
      "Train Epoch: 142 [28160/50000 (62%)]\tLoss: 0.065328, Accuracy: 98.05\n",
      "Train Epoch: 142 [29440/50000 (65%)]\tLoss: 0.024012, Accuracy: 98.83\n",
      "Train Epoch: 142 [30720/50000 (68%)]\tLoss: 0.024484, Accuracy: 99.22\n",
      "Train Epoch: 142 [32000/50000 (71%)]\tLoss: 0.005715, Accuracy: 100.00\n",
      "Train Epoch: 142 [33280/50000 (74%)]\tLoss: 0.014250, Accuracy: 100.00\n",
      "Train Epoch: 142 [34560/50000 (77%)]\tLoss: 0.022204, Accuracy: 99.22\n",
      "Train Epoch: 142 [35840/50000 (80%)]\tLoss: 0.054831, Accuracy: 97.66\n",
      "Train Epoch: 142 [37120/50000 (82%)]\tLoss: 0.023855, Accuracy: 99.22\n",
      "Train Epoch: 142 [38400/50000 (85%)]\tLoss: 0.035822, Accuracy: 98.83\n",
      "Train Epoch: 142 [39680/50000 (88%)]\tLoss: 0.021335, Accuracy: 98.83\n",
      "Train Epoch: 142 [40960/50000 (91%)]\tLoss: 0.035801, Accuracy: 98.44\n",
      "Train Epoch: 142 [42240/50000 (94%)]\tLoss: 0.003918, Accuracy: 100.00\n",
      "Train Epoch: 142 [43520/50000 (97%)]\tLoss: 0.038468, Accuracy: 98.44\n",
      "Train Epoch: 142 [35000/50000 (99%)]\tLoss: 0.006925, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5721, Accuracy: 4463/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.30694079399109 s]\n",
      "Train Epoch: 143 [0/50000 (0%)]\tLoss: 0.016464, Accuracy: 99.22\n",
      "Train Epoch: 143 [1280/50000 (3%)]\tLoss: 0.015371, Accuracy: 99.22\n",
      "Train Epoch: 143 [2560/50000 (6%)]\tLoss: 0.013805, Accuracy: 99.22\n",
      "Train Epoch: 143 [3840/50000 (9%)]\tLoss: 0.021252, Accuracy: 99.22\n",
      "Train Epoch: 143 [5120/50000 (11%)]\tLoss: 0.020939, Accuracy: 99.61\n",
      "Train Epoch: 143 [6400/50000 (14%)]\tLoss: 0.026719, Accuracy: 98.83\n",
      "Train Epoch: 143 [7680/50000 (17%)]\tLoss: 0.007632, Accuracy: 99.61\n",
      "Train Epoch: 143 [8960/50000 (20%)]\tLoss: 0.025033, Accuracy: 99.61\n",
      "Train Epoch: 143 [10240/50000 (23%)]\tLoss: 0.006426, Accuracy: 100.00\n",
      "Train Epoch: 143 [11520/50000 (26%)]\tLoss: 0.026786, Accuracy: 98.83\n",
      "Train Epoch: 143 [12800/50000 (28%)]\tLoss: 0.037508, Accuracy: 98.05\n",
      "Train Epoch: 143 [14080/50000 (31%)]\tLoss: 0.089559, Accuracy: 98.05\n",
      "Train Epoch: 143 [15360/50000 (34%)]\tLoss: 0.011708, Accuracy: 99.61\n",
      "Train Epoch: 143 [16640/50000 (37%)]\tLoss: 0.015049, Accuracy: 99.61\n",
      "Train Epoch: 143 [17920/50000 (40%)]\tLoss: 0.024865, Accuracy: 98.83\n",
      "Train Epoch: 143 [19200/50000 (43%)]\tLoss: 0.021554, Accuracy: 98.83\n",
      "Train Epoch: 143 [20480/50000 (45%)]\tLoss: 0.019182, Accuracy: 99.22\n",
      "Train Epoch: 143 [21760/50000 (48%)]\tLoss: 0.009613, Accuracy: 99.61\n",
      "Train Epoch: 143 [23040/50000 (51%)]\tLoss: 0.007841, Accuracy: 99.61\n",
      "Train Epoch: 143 [24320/50000 (54%)]\tLoss: 0.013009, Accuracy: 99.61\n",
      "Train Epoch: 143 [25600/50000 (57%)]\tLoss: 0.025028, Accuracy: 99.61\n",
      "Train Epoch: 143 [26880/50000 (60%)]\tLoss: 0.046323, Accuracy: 98.44\n",
      "Train Epoch: 143 [28160/50000 (62%)]\tLoss: 0.019659, Accuracy: 99.22\n",
      "Train Epoch: 143 [29440/50000 (65%)]\tLoss: 0.024378, Accuracy: 99.22\n",
      "Train Epoch: 143 [30720/50000 (68%)]\tLoss: 0.005109, Accuracy: 100.00\n",
      "Train Epoch: 143 [32000/50000 (71%)]\tLoss: 0.039740, Accuracy: 98.44\n",
      "Train Epoch: 143 [33280/50000 (74%)]\tLoss: 0.042676, Accuracy: 98.83\n",
      "Train Epoch: 143 [34560/50000 (77%)]\tLoss: 0.015517, Accuracy: 99.61\n",
      "Train Epoch: 143 [35840/50000 (80%)]\tLoss: 0.066210, Accuracy: 97.27\n",
      "Train Epoch: 143 [37120/50000 (82%)]\tLoss: 0.007658, Accuracy: 100.00\n",
      "Train Epoch: 143 [38400/50000 (85%)]\tLoss: 0.007309, Accuracy: 99.61\n",
      "Train Epoch: 143 [39680/50000 (88%)]\tLoss: 0.019441, Accuracy: 99.22\n",
      "Train Epoch: 143 [40960/50000 (91%)]\tLoss: 0.014935, Accuracy: 99.61\n",
      "Train Epoch: 143 [42240/50000 (94%)]\tLoss: 0.021529, Accuracy: 99.22\n",
      "Train Epoch: 143 [43520/50000 (97%)]\tLoss: 0.023953, Accuracy: 98.83\n",
      "Train Epoch: 143 [35000/50000 (99%)]\tLoss: 0.051325, Accuracy: 97.50\n",
      "\n",
      "Validation set: Average loss: 0.5750, Accuracy: 4476/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.305058002471924 s]\n",
      "Train Epoch: 144 [0/50000 (0%)]\tLoss: 0.027881, Accuracy: 99.22\n",
      "Train Epoch: 144 [1280/50000 (3%)]\tLoss: 0.023547, Accuracy: 99.61\n",
      "Train Epoch: 144 [2560/50000 (6%)]\tLoss: 0.024309, Accuracy: 99.22\n",
      "Train Epoch: 144 [3840/50000 (9%)]\tLoss: 0.028057, Accuracy: 99.22\n",
      "Train Epoch: 144 [5120/50000 (11%)]\tLoss: 0.038611, Accuracy: 98.83\n",
      "Train Epoch: 144 [6400/50000 (14%)]\tLoss: 0.028873, Accuracy: 98.05\n",
      "Train Epoch: 144 [7680/50000 (17%)]\tLoss: 0.031076, Accuracy: 98.44\n",
      "Train Epoch: 144 [8960/50000 (20%)]\tLoss: 0.020658, Accuracy: 99.22\n",
      "Train Epoch: 144 [10240/50000 (23%)]\tLoss: 0.007317, Accuracy: 99.61\n",
      "Train Epoch: 144 [11520/50000 (26%)]\tLoss: 0.015931, Accuracy: 99.22\n",
      "Train Epoch: 144 [12800/50000 (28%)]\tLoss: 0.011961, Accuracy: 99.61\n",
      "Train Epoch: 144 [14080/50000 (31%)]\tLoss: 0.019693, Accuracy: 99.22\n",
      "Train Epoch: 144 [15360/50000 (34%)]\tLoss: 0.039956, Accuracy: 98.44\n",
      "Train Epoch: 144 [16640/50000 (37%)]\tLoss: 0.012657, Accuracy: 99.22\n",
      "Train Epoch: 144 [17920/50000 (40%)]\tLoss: 0.014797, Accuracy: 98.83\n",
      "Train Epoch: 144 [19200/50000 (43%)]\tLoss: 0.014295, Accuracy: 99.61\n",
      "Train Epoch: 144 [20480/50000 (45%)]\tLoss: 0.037523, Accuracy: 98.44\n",
      "Train Epoch: 144 [21760/50000 (48%)]\tLoss: 0.013124, Accuracy: 99.61\n",
      "Train Epoch: 144 [23040/50000 (51%)]\tLoss: 0.012018, Accuracy: 99.61\n",
      "Train Epoch: 144 [24320/50000 (54%)]\tLoss: 0.014550, Accuracy: 99.61\n",
      "Train Epoch: 144 [25600/50000 (57%)]\tLoss: 0.002712, Accuracy: 100.00\n",
      "Train Epoch: 144 [26880/50000 (60%)]\tLoss: 0.011818, Accuracy: 99.61\n",
      "Train Epoch: 144 [28160/50000 (62%)]\tLoss: 0.020694, Accuracy: 98.83\n",
      "Train Epoch: 144 [29440/50000 (65%)]\tLoss: 0.014719, Accuracy: 99.61\n",
      "Train Epoch: 144 [30720/50000 (68%)]\tLoss: 0.037115, Accuracy: 98.83\n",
      "Train Epoch: 144 [32000/50000 (71%)]\tLoss: 0.012224, Accuracy: 99.61\n",
      "Train Epoch: 144 [33280/50000 (74%)]\tLoss: 0.006990, Accuracy: 99.61\n",
      "Train Epoch: 144 [34560/50000 (77%)]\tLoss: 0.009840, Accuracy: 99.61\n",
      "Train Epoch: 144 [35840/50000 (80%)]\tLoss: 0.025854, Accuracy: 98.05\n",
      "Train Epoch: 144 [37120/50000 (82%)]\tLoss: 0.030992, Accuracy: 99.22\n",
      "Train Epoch: 144 [38400/50000 (85%)]\tLoss: 0.002494, Accuracy: 100.00\n",
      "Train Epoch: 144 [39680/50000 (88%)]\tLoss: 0.019797, Accuracy: 99.22\n",
      "Train Epoch: 144 [40960/50000 (91%)]\tLoss: 0.014303, Accuracy: 99.61\n",
      "Train Epoch: 144 [42240/50000 (94%)]\tLoss: 0.015699, Accuracy: 99.61\n",
      "Train Epoch: 144 [43520/50000 (97%)]\tLoss: 0.006669, Accuracy: 100.00\n",
      "Train Epoch: 144 [35000/50000 (99%)]\tLoss: 0.012973, Accuracy: 99.50\n",
      "\n",
      "Validation set: Average loss: 0.5703, Accuracy: 4464/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.335841178894043 s]\n",
      "Train Epoch: 145 [0/50000 (0%)]\tLoss: 0.004285, Accuracy: 100.00\n",
      "Train Epoch: 145 [1280/50000 (3%)]\tLoss: 0.020980, Accuracy: 99.61\n",
      "Train Epoch: 145 [2560/50000 (6%)]\tLoss: 0.014594, Accuracy: 99.61\n",
      "Train Epoch: 145 [3840/50000 (9%)]\tLoss: 0.032308, Accuracy: 98.83\n",
      "Train Epoch: 145 [5120/50000 (11%)]\tLoss: 0.032069, Accuracy: 98.83\n",
      "Train Epoch: 145 [6400/50000 (14%)]\tLoss: 0.023689, Accuracy: 98.83\n",
      "Train Epoch: 145 [7680/50000 (17%)]\tLoss: 0.025533, Accuracy: 99.22\n",
      "Train Epoch: 145 [8960/50000 (20%)]\tLoss: 0.040190, Accuracy: 98.83\n",
      "Train Epoch: 145 [10240/50000 (23%)]\tLoss: 0.014083, Accuracy: 99.61\n",
      "Train Epoch: 145 [11520/50000 (26%)]\tLoss: 0.040569, Accuracy: 98.44\n",
      "Train Epoch: 145 [12800/50000 (28%)]\tLoss: 0.049267, Accuracy: 97.66\n",
      "Train Epoch: 145 [14080/50000 (31%)]\tLoss: 0.020015, Accuracy: 99.22\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 145 [15360/50000 (34%)]\tLoss: 0.031205, Accuracy: 98.44\n",
      "Train Epoch: 145 [16640/50000 (37%)]\tLoss: 0.009341, Accuracy: 100.00\n",
      "Train Epoch: 145 [17920/50000 (40%)]\tLoss: 0.046004, Accuracy: 98.44\n",
      "Train Epoch: 145 [19200/50000 (43%)]\tLoss: 0.004463, Accuracy: 100.00\n",
      "Train Epoch: 145 [20480/50000 (45%)]\tLoss: 0.015201, Accuracy: 99.61\n",
      "Train Epoch: 145 [21760/50000 (48%)]\tLoss: 0.017726, Accuracy: 99.22\n",
      "Train Epoch: 145 [23040/50000 (51%)]\tLoss: 0.012779, Accuracy: 99.22\n",
      "Train Epoch: 145 [24320/50000 (54%)]\tLoss: 0.014498, Accuracy: 99.61\n",
      "Train Epoch: 145 [25600/50000 (57%)]\tLoss: 0.018737, Accuracy: 99.61\n",
      "Train Epoch: 145 [26880/50000 (60%)]\tLoss: 0.025845, Accuracy: 99.22\n",
      "Train Epoch: 145 [28160/50000 (62%)]\tLoss: 0.013072, Accuracy: 99.61\n",
      "Train Epoch: 145 [29440/50000 (65%)]\tLoss: 0.011494, Accuracy: 99.61\n",
      "Train Epoch: 145 [30720/50000 (68%)]\tLoss: 0.008277, Accuracy: 99.61\n",
      "Train Epoch: 145 [32000/50000 (71%)]\tLoss: 0.023960, Accuracy: 98.83\n",
      "Train Epoch: 145 [33280/50000 (74%)]\tLoss: 0.031654, Accuracy: 99.22\n",
      "Train Epoch: 145 [34560/50000 (77%)]\tLoss: 0.018382, Accuracy: 99.22\n",
      "Train Epoch: 145 [35840/50000 (80%)]\tLoss: 0.023685, Accuracy: 99.61\n",
      "Train Epoch: 145 [37120/50000 (82%)]\tLoss: 0.042794, Accuracy: 99.22\n",
      "Train Epoch: 145 [38400/50000 (85%)]\tLoss: 0.006504, Accuracy: 99.61\n",
      "Train Epoch: 145 [39680/50000 (88%)]\tLoss: 0.030640, Accuracy: 98.44\n",
      "Train Epoch: 145 [40960/50000 (91%)]\tLoss: 0.031012, Accuracy: 98.83\n",
      "Train Epoch: 145 [42240/50000 (94%)]\tLoss: 0.012094, Accuracy: 99.61\n",
      "Train Epoch: 145 [43520/50000 (97%)]\tLoss: 0.014059, Accuracy: 99.61\n",
      "Train Epoch: 145 [35000/50000 (99%)]\tLoss: 0.021830, Accuracy: 98.50\n",
      "\n",
      "Validation set: Average loss: 0.5796, Accuracy: 4468/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.35237693786621 s]\n",
      "Train Epoch: 146 [0/50000 (0%)]\tLoss: 0.007788, Accuracy: 100.00\n",
      "Train Epoch: 146 [1280/50000 (3%)]\tLoss: 0.023519, Accuracy: 99.22\n",
      "Train Epoch: 146 [2560/50000 (6%)]\tLoss: 0.025565, Accuracy: 98.44\n",
      "Train Epoch: 146 [3840/50000 (9%)]\tLoss: 0.012708, Accuracy: 100.00\n",
      "Train Epoch: 146 [5120/50000 (11%)]\tLoss: 0.008481, Accuracy: 99.61\n",
      "Train Epoch: 146 [6400/50000 (14%)]\tLoss: 0.002637, Accuracy: 100.00\n",
      "Train Epoch: 146 [7680/50000 (17%)]\tLoss: 0.013167, Accuracy: 98.83\n",
      "Train Epoch: 146 [8960/50000 (20%)]\tLoss: 0.021583, Accuracy: 99.22\n",
      "Train Epoch: 146 [10240/50000 (23%)]\tLoss: 0.021726, Accuracy: 99.22\n",
      "Train Epoch: 146 [11520/50000 (26%)]\tLoss: 0.016645, Accuracy: 99.22\n",
      "Train Epoch: 146 [12800/50000 (28%)]\tLoss: 0.004772, Accuracy: 100.00\n",
      "Train Epoch: 146 [14080/50000 (31%)]\tLoss: 0.034399, Accuracy: 98.44\n",
      "Train Epoch: 146 [15360/50000 (34%)]\tLoss: 0.012027, Accuracy: 99.22\n",
      "Train Epoch: 146 [16640/50000 (37%)]\tLoss: 0.008563, Accuracy: 100.00\n",
      "Train Epoch: 146 [17920/50000 (40%)]\tLoss: 0.021858, Accuracy: 99.61\n",
      "Train Epoch: 146 [19200/50000 (43%)]\tLoss: 0.027555, Accuracy: 99.22\n",
      "Train Epoch: 146 [20480/50000 (45%)]\tLoss: 0.009683, Accuracy: 100.00\n",
      "Train Epoch: 146 [21760/50000 (48%)]\tLoss: 0.008049, Accuracy: 100.00\n",
      "Train Epoch: 146 [23040/50000 (51%)]\tLoss: 0.017517, Accuracy: 99.61\n",
      "Train Epoch: 146 [24320/50000 (54%)]\tLoss: 0.016486, Accuracy: 99.61\n",
      "Train Epoch: 146 [25600/50000 (57%)]\tLoss: 0.034101, Accuracy: 98.83\n",
      "Train Epoch: 146 [26880/50000 (60%)]\tLoss: 0.013523, Accuracy: 99.61\n",
      "Train Epoch: 146 [28160/50000 (62%)]\tLoss: 0.006648, Accuracy: 100.00\n",
      "Train Epoch: 146 [29440/50000 (65%)]\tLoss: 0.034986, Accuracy: 98.83\n",
      "Train Epoch: 146 [30720/50000 (68%)]\tLoss: 0.006035, Accuracy: 100.00\n",
      "Train Epoch: 146 [32000/50000 (71%)]\tLoss: 0.018357, Accuracy: 99.22\n",
      "Train Epoch: 146 [33280/50000 (74%)]\tLoss: 0.030237, Accuracy: 98.83\n",
      "Train Epoch: 146 [34560/50000 (77%)]\tLoss: 0.031326, Accuracy: 98.44\n",
      "Train Epoch: 146 [35840/50000 (80%)]\tLoss: 0.005573, Accuracy: 100.00\n",
      "Train Epoch: 146 [37120/50000 (82%)]\tLoss: 0.009259, Accuracy: 99.61\n",
      "Train Epoch: 146 [38400/50000 (85%)]\tLoss: 0.015968, Accuracy: 99.22\n",
      "Train Epoch: 146 [39680/50000 (88%)]\tLoss: 0.004282, Accuracy: 100.00\n",
      "Train Epoch: 146 [40960/50000 (91%)]\tLoss: 0.010811, Accuracy: 99.61\n",
      "Train Epoch: 146 [42240/50000 (94%)]\tLoss: 0.018713, Accuracy: 99.61\n",
      "Train Epoch: 146 [43520/50000 (97%)]\tLoss: 0.051914, Accuracy: 98.44\n",
      "Train Epoch: 146 [35000/50000 (99%)]\tLoss: 0.021631, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5723, Accuracy: 4478/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.347144842147827 s]\n",
      "Train Epoch: 147 [0/50000 (0%)]\tLoss: 0.009097, Accuracy: 100.00\n",
      "Train Epoch: 147 [1280/50000 (3%)]\tLoss: 0.047466, Accuracy: 98.44\n",
      "Train Epoch: 147 [2560/50000 (6%)]\tLoss: 0.016024, Accuracy: 99.61\n",
      "Train Epoch: 147 [3840/50000 (9%)]\tLoss: 0.015346, Accuracy: 99.61\n",
      "Train Epoch: 147 [5120/50000 (11%)]\tLoss: 0.014117, Accuracy: 99.61\n",
      "Train Epoch: 147 [6400/50000 (14%)]\tLoss: 0.024067, Accuracy: 99.22\n",
      "Train Epoch: 147 [7680/50000 (17%)]\tLoss: 0.012941, Accuracy: 100.00\n",
      "Train Epoch: 147 [8960/50000 (20%)]\tLoss: 0.037829, Accuracy: 98.05\n",
      "Train Epoch: 147 [10240/50000 (23%)]\tLoss: 0.048710, Accuracy: 98.05\n",
      "Train Epoch: 147 [11520/50000 (26%)]\tLoss: 0.020281, Accuracy: 99.22\n",
      "Train Epoch: 147 [12800/50000 (28%)]\tLoss: 0.011055, Accuracy: 99.61\n",
      "Train Epoch: 147 [14080/50000 (31%)]\tLoss: 0.018451, Accuracy: 98.83\n",
      "Train Epoch: 147 [15360/50000 (34%)]\tLoss: 0.070135, Accuracy: 97.27\n",
      "Train Epoch: 147 [16640/50000 (37%)]\tLoss: 0.026243, Accuracy: 98.44\n",
      "Train Epoch: 147 [17920/50000 (40%)]\tLoss: 0.038771, Accuracy: 99.61\n",
      "Train Epoch: 147 [19200/50000 (43%)]\tLoss: 0.018163, Accuracy: 99.22\n",
      "Train Epoch: 147 [20480/50000 (45%)]\tLoss: 0.028077, Accuracy: 99.22\n",
      "Train Epoch: 147 [21760/50000 (48%)]\tLoss: 0.015967, Accuracy: 99.22\n",
      "Train Epoch: 147 [23040/50000 (51%)]\tLoss: 0.017279, Accuracy: 99.22\n",
      "Train Epoch: 147 [24320/50000 (54%)]\tLoss: 0.045417, Accuracy: 98.83\n",
      "Train Epoch: 147 [25600/50000 (57%)]\tLoss: 0.023400, Accuracy: 99.22\n",
      "Train Epoch: 147 [26880/50000 (60%)]\tLoss: 0.025786, Accuracy: 99.61\n",
      "Train Epoch: 147 [28160/50000 (62%)]\tLoss: 0.044606, Accuracy: 98.83\n",
      "Train Epoch: 147 [29440/50000 (65%)]\tLoss: 0.018019, Accuracy: 99.22\n",
      "Train Epoch: 147 [30720/50000 (68%)]\tLoss: 0.010614, Accuracy: 99.61\n",
      "Train Epoch: 147 [32000/50000 (71%)]\tLoss: 0.011733, Accuracy: 99.61\n",
      "Train Epoch: 147 [33280/50000 (74%)]\tLoss: 0.026184, Accuracy: 99.61\n",
      "Train Epoch: 147 [34560/50000 (77%)]\tLoss: 0.005881, Accuracy: 100.00\n",
      "Train Epoch: 147 [35840/50000 (80%)]\tLoss: 0.004241, Accuracy: 100.00\n",
      "Train Epoch: 147 [37120/50000 (82%)]\tLoss: 0.034073, Accuracy: 98.83\n",
      "Train Epoch: 147 [38400/50000 (85%)]\tLoss: 0.018717, Accuracy: 99.22\n",
      "Train Epoch: 147 [39680/50000 (88%)]\tLoss: 0.026583, Accuracy: 99.22\n",
      "Train Epoch: 147 [40960/50000 (91%)]\tLoss: 0.025308, Accuracy: 99.22\n",
      "Train Epoch: 147 [42240/50000 (94%)]\tLoss: 0.008503, Accuracy: 100.00\n",
      "Train Epoch: 147 [43520/50000 (97%)]\tLoss: 0.028867, Accuracy: 99.22\n",
      "Train Epoch: 147 [35000/50000 (99%)]\tLoss: 0.012330, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5727, Accuracy: 4469/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.364238262176514 s]\n",
      "Train Epoch: 148 [0/50000 (0%)]\tLoss: 0.020313, Accuracy: 99.61\n",
      "Train Epoch: 148 [1280/50000 (3%)]\tLoss: 0.020353, Accuracy: 98.83\n",
      "Train Epoch: 148 [2560/50000 (6%)]\tLoss: 0.011970, Accuracy: 99.61\n",
      "Train Epoch: 148 [3840/50000 (9%)]\tLoss: 0.042884, Accuracy: 98.05\n",
      "Train Epoch: 148 [5120/50000 (11%)]\tLoss: 0.014417, Accuracy: 99.61\n",
      "Train Epoch: 148 [6400/50000 (14%)]\tLoss: 0.036290, Accuracy: 98.83\n",
      "Train Epoch: 148 [7680/50000 (17%)]\tLoss: 0.010854, Accuracy: 99.61\n",
      "Train Epoch: 148 [8960/50000 (20%)]\tLoss: 0.038244, Accuracy: 98.44\n",
      "Train Epoch: 148 [10240/50000 (23%)]\tLoss: 0.013837, Accuracy: 99.61\n",
      "Train Epoch: 148 [11520/50000 (26%)]\tLoss: 0.024759, Accuracy: 98.83\n",
      "Train Epoch: 148 [12800/50000 (28%)]\tLoss: 0.027030, Accuracy: 98.83\n",
      "Train Epoch: 148 [14080/50000 (31%)]\tLoss: 0.023826, Accuracy: 99.22\n",
      "Train Epoch: 148 [15360/50000 (34%)]\tLoss: 0.013826, Accuracy: 99.61\n",
      "Train Epoch: 148 [16640/50000 (37%)]\tLoss: 0.053709, Accuracy: 98.44\n",
      "Train Epoch: 148 [17920/50000 (40%)]\tLoss: 0.008292, Accuracy: 100.00\n",
      "Train Epoch: 148 [19200/50000 (43%)]\tLoss: 0.035796, Accuracy: 98.05\n",
      "Train Epoch: 148 [20480/50000 (45%)]\tLoss: 0.033991, Accuracy: 98.83\n",
      "Train Epoch: 148 [21760/50000 (48%)]\tLoss: 0.011091, Accuracy: 99.61\n",
      "Train Epoch: 148 [23040/50000 (51%)]\tLoss: 0.009554, Accuracy: 100.00\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 148 [24320/50000 (54%)]\tLoss: 0.036666, Accuracy: 98.44\n",
      "Train Epoch: 148 [25600/50000 (57%)]\tLoss: 0.012172, Accuracy: 99.61\n",
      "Train Epoch: 148 [26880/50000 (60%)]\tLoss: 0.027374, Accuracy: 99.22\n",
      "Train Epoch: 148 [28160/50000 (62%)]\tLoss: 0.007565, Accuracy: 100.00\n",
      "Train Epoch: 148 [29440/50000 (65%)]\tLoss: 0.008084, Accuracy: 99.61\n",
      "Train Epoch: 148 [30720/50000 (68%)]\tLoss: 0.017591, Accuracy: 99.22\n",
      "Train Epoch: 148 [32000/50000 (71%)]\tLoss: 0.042466, Accuracy: 98.44\n",
      "Train Epoch: 148 [33280/50000 (74%)]\tLoss: 0.012539, Accuracy: 99.61\n",
      "Train Epoch: 148 [34560/50000 (77%)]\tLoss: 0.050277, Accuracy: 97.27\n",
      "Train Epoch: 148 [35840/50000 (80%)]\tLoss: 0.026891, Accuracy: 99.61\n",
      "Train Epoch: 148 [37120/50000 (82%)]\tLoss: 0.019270, Accuracy: 99.61\n",
      "Train Epoch: 148 [38400/50000 (85%)]\tLoss: 0.023822, Accuracy: 98.44\n",
      "Train Epoch: 148 [39680/50000 (88%)]\tLoss: 0.011936, Accuracy: 100.00\n",
      "Train Epoch: 148 [40960/50000 (91%)]\tLoss: 0.026969, Accuracy: 99.22\n",
      "Train Epoch: 148 [42240/50000 (94%)]\tLoss: 0.013142, Accuracy: 99.22\n",
      "Train Epoch: 148 [43520/50000 (97%)]\tLoss: 0.021662, Accuracy: 99.61\n",
      "Train Epoch: 148 [35000/50000 (99%)]\tLoss: 0.008549, Accuracy: 100.00\n",
      "\n",
      "Validation set: Average loss: 0.5793, Accuracy: 4463/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.354016304016113 s]\n",
      "Train Epoch: 149 [0/50000 (0%)]\tLoss: 0.030955, Accuracy: 99.61\n",
      "Train Epoch: 149 [1280/50000 (3%)]\tLoss: 0.012940, Accuracy: 99.61\n",
      "Train Epoch: 149 [2560/50000 (6%)]\tLoss: 0.022842, Accuracy: 98.83\n",
      "Train Epoch: 149 [3840/50000 (9%)]\tLoss: 0.021620, Accuracy: 98.83\n",
      "Train Epoch: 149 [5120/50000 (11%)]\tLoss: 0.026299, Accuracy: 98.83\n",
      "Train Epoch: 149 [6400/50000 (14%)]\tLoss: 0.006471, Accuracy: 100.00\n",
      "Train Epoch: 149 [7680/50000 (17%)]\tLoss: 0.029995, Accuracy: 99.22\n",
      "Train Epoch: 149 [8960/50000 (20%)]\tLoss: 0.030642, Accuracy: 98.83\n",
      "Train Epoch: 149 [10240/50000 (23%)]\tLoss: 0.013087, Accuracy: 99.22\n",
      "Train Epoch: 149 [11520/50000 (26%)]\tLoss: 0.010131, Accuracy: 100.00\n",
      "Train Epoch: 149 [12800/50000 (28%)]\tLoss: 0.033396, Accuracy: 98.44\n",
      "Train Epoch: 149 [14080/50000 (31%)]\tLoss: 0.081951, Accuracy: 97.27\n",
      "Train Epoch: 149 [15360/50000 (34%)]\tLoss: 0.013251, Accuracy: 99.61\n",
      "Train Epoch: 149 [16640/50000 (37%)]\tLoss: 0.011448, Accuracy: 99.61\n",
      "Train Epoch: 149 [17920/50000 (40%)]\tLoss: 0.022318, Accuracy: 99.22\n",
      "Train Epoch: 149 [19200/50000 (43%)]\tLoss: 0.006800, Accuracy: 99.61\n",
      "Train Epoch: 149 [20480/50000 (45%)]\tLoss: 0.022353, Accuracy: 98.83\n",
      "Train Epoch: 149 [21760/50000 (48%)]\tLoss: 0.023404, Accuracy: 98.83\n",
      "Train Epoch: 149 [23040/50000 (51%)]\tLoss: 0.007999, Accuracy: 100.00\n",
      "Train Epoch: 149 [24320/50000 (54%)]\tLoss: 0.018268, Accuracy: 99.61\n",
      "Train Epoch: 149 [25600/50000 (57%)]\tLoss: 0.004704, Accuracy: 100.00\n",
      "Train Epoch: 149 [26880/50000 (60%)]\tLoss: 0.014857, Accuracy: 99.22\n",
      "Train Epoch: 149 [28160/50000 (62%)]\tLoss: 0.004101, Accuracy: 100.00\n",
      "Train Epoch: 149 [29440/50000 (65%)]\tLoss: 0.013560, Accuracy: 99.61\n",
      "Train Epoch: 149 [30720/50000 (68%)]\tLoss: 0.007933, Accuracy: 100.00\n",
      "Train Epoch: 149 [32000/50000 (71%)]\tLoss: 0.034865, Accuracy: 98.83\n",
      "Train Epoch: 149 [33280/50000 (74%)]\tLoss: 0.023053, Accuracy: 98.83\n",
      "Train Epoch: 149 [34560/50000 (77%)]\tLoss: 0.010351, Accuracy: 99.61\n",
      "Train Epoch: 149 [35840/50000 (80%)]\tLoss: 0.011016, Accuracy: 100.00\n",
      "Train Epoch: 149 [37120/50000 (82%)]\tLoss: 0.019699, Accuracy: 99.22\n",
      "Train Epoch: 149 [38400/50000 (85%)]\tLoss: 0.027637, Accuracy: 98.83\n",
      "Train Epoch: 149 [39680/50000 (88%)]\tLoss: 0.007503, Accuracy: 99.61\n",
      "Train Epoch: 149 [40960/50000 (91%)]\tLoss: 0.009101, Accuracy: 100.00\n",
      "Train Epoch: 149 [42240/50000 (94%)]\tLoss: 0.018246, Accuracy: 99.22\n",
      "Train Epoch: 149 [43520/50000 (97%)]\tLoss: 0.030277, Accuracy: 98.83\n",
      "Train Epoch: 149 [35000/50000 (99%)]\tLoss: 0.025757, Accuracy: 99.00\n",
      "\n",
      "Validation set: Average loss: 0.5756, Accuracy: 4473/5000 (89.00%)\n",
      "\n",
      "the time of this epoch:[21.353271007537842 s]\n",
      "\n",
      "Test set: Average loss: 0.6688, Accuracy: 8915/10000 (89.15%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Fantastic logger for tensorboard and pytorch, \n",
    "# run tensorboard by opening a new terminal and run \"tensorboard --logdir runs\"\n",
    "# open tensorboard at http://localhost:6006/\n",
    "from tensorboardX import SummaryWriter\n",
    "best_loss = None\n",
    "best_acc = None\n",
    "\n",
    "import time \n",
    "SINCE=time.time()\n",
    "\n",
    "for epoch in range(max_epoch):\n",
    "    train(epoch)\n",
    "    \n",
    "    loss, accuracy = validate(epoch)\n",
    "    best_loss, best_acc = save_best(loss, accuracy, best_loss, best_acc)\n",
    "    \n",
    "    NOW=time.time() \n",
    "    DURINGS=NOW-SINCE\n",
    "    SINCE=NOW\n",
    "    print(\"the time of this epoch:[{} s]\".format(DURINGS))\n",
    "    \n",
    "# writer = SummaryWriter()\n",
    "# writer.export_scalars_to_json(\"./all_scalars.json\")\n",
    "\n",
    "# writer.close()\n",
    "\n",
    "#---------------------------- Test ------------------------------\n",
    "test(epoch)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 3: Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Test set: Average loss: 0.6860, Accuracy: 8937/10000 (89.37%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "test(epoch)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第一次 scale 位于[0,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "![](http://op4a94iq8.bkt.clouddn.com/18-7-14/70206949.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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X31/fe9LvZ2vJWUnW0hr5uH35k3EJth8Y1/tcVGLf/6o7fBVAgd5VXN0TfcmyvzdZ82xC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\n/x9BnCF17x72RAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看训练过程的信息\n",
    "import  matplotlib.pyplot as plt\n",
    "\n",
    "def parse(in_file,flag):\n",
    "    num=-1\n",
    "    ys=list()\n",
    "    xs=list()\n",
    "    losses=list()\n",
    "    with open(in_file,\"r\") as reader:\n",
    "        for aLine in reader:\n",
    "            #print(aLine)\n",
    "\n",
    "            res=[e for e in aLine.strip('\\n').split(\" \")]\n",
    "            if res[0]==\"Train\" and flag==\"Train\":\n",
    "                num=num+1\n",
    "                ys.append(float(res[-1]))\n",
    "                xs.append(int(num))\n",
    "                losses.append(float(res[-3].split(',')[0]))\n",
    "            if res[0]==\"Validation\" and flag==\"Validation\":\n",
    "                num=num+1\n",
    "                xs.append(int(num))\n",
    "                tmp=[float(e) for e in res[-2].split('/')]\n",
    "                ys.append(100*float(tmp[0]/tmp[1]))\n",
    "                losses.append(float(res[-4].split(',')[0]))\n",
    "\n",
    "    plt.figure(1)\n",
    "    plt.plot(xs,ys,'ro')\n",
    "\n",
    "\n",
    "    plt.figure(2)\n",
    "    plt.plot(xs, losses, 'ro')\n",
    "    plt.show()\n",
    "\n",
    "def main():\n",
    "    in_file=\"D://INFO.txt\"\n",
    "    # 显示训练阶段的正确率和Loss信息\n",
    "    parse(in_file,\"Train\") # \"Validation\"\n",
    "    # 显示验证阶段的正确率和Loss信息\n",
    "    #parse(in_file,\"Validation\") # \"Validation\"\n",
    "\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B79YtXUHXO6N9gp5FvFmdL+sbhwt9tG0D0thdvmmRRgx9yy2lkO+wA3DJJfb2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\naRBY0BmGYRqE/w/U/zxNDJVCvAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hDBNo+60g7Jjl3rBJxD1uoPQ49t5b3+h2SMt47qbUbxRpPfcwcTcC0tlZ3JDt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\ngFDcCSGkAaG4E0JIA0JxJ4SQBuT/AHC9SchdaANwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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88UeowtCh9vi112J3VkyG4mKbi3XaNJg9O3H78fq+cznJE39Eaakl2TPOsKtY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\nDuAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Med4Y4zPG+AoKCiw4NJFH/fznWideskQX0LbK2LE6oJgjpQl89JH22xk/Xn+/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\n/wPtS+GMghk59AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看训练过程的信息\n",
    "import  matplotlib.pyplot as plt\n",
    "\n",
    "def parse(in_file,flag):\n",
    "    num=-1\n",
    "    ys=list()\n",
    "    xs=list()\n",
    "    losses=list()\n",
    "    with open(in_file,\"r\") as reader:\n",
    "        for aLine in reader:\n",
    "            #print(aLine)\n",
    "\n",
    "            res=[e for e in aLine.strip('\\n').split(\" \")]\n",
    "            if res[0]==\"Train\" and flag==\"Train\":\n",
    "                num=num+1\n",
    "                ys.append(float(res[-1]))\n",
    "                xs.append(int(num))\n",
    "                losses.append(float(res[-3].split(',')[0]))\n",
    "            if res[0]==\"Validation\" and flag==\"Validation\":\n",
    "                num=num+1\n",
    "                xs.append(int(num))\n",
    "                tmp=[float(e) for e in res[-2].split('/')]\n",
    "                ys.append(100*float(tmp[0]/tmp[1]))\n",
    "                losses.append(float(res[-4].split(',')[0]))\n",
    "\n",
    "    plt.figure(1)\n",
    "    plt.plot(xs,ys,'r-')\n",
    "\n",
    "\n",
    "    plt.figure(2)\n",
    "    plt.plot(xs, losses, 'r-')\n",
    "    plt.show()\n",
    "\n",
    "def main():\n",
    "    in_file=\"D://INFO.txt\"\n",
    "    # 显示训练阶段的正确率和Loss信息\n",
    "    parse(in_file,\"Train\") # \"Validation\"\n",
    "    # 显示验证阶段的正确率和Loss信息\n",
    "    parse(in_file,\"Validation\") # \"Validation\"\n",
    "\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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