diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.caffemodel b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.caffemodel
deleted file mode 100644
index a555f77..0000000
Binary files a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.caffemodel and /dev/null differ
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.prototxt b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.prototxt
deleted file mode 100644
index 8dbbc91..0000000
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m1.prototxt	
+++ /dev/null
@@ -1,387 +0,0 @@
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param {
-    shape {
-      dim: 1
-      dim: 3
-      dim: 224
-      dim: 224
-    }
-  }
-}
-layer {
-  name: "Conv_0"
-  type: "Convolution"
-  bottom: "data"
-  top: "input.3"
-  convolution_param {
-    num_output: 32
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_1"
-  type: "ReLU"
-  bottom: "input.3"
-  top: "onnx::Conv_84"
-}
-layer {
-  name: "Conv_2"
-  type: "Convolution"
-  bottom: "onnx::Conv_84"
-  top: "input.11"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_3"
-  type: "ReLU"
-  bottom: "input.11"
-  top: "onnx::Conv_87"
-}
-layer {
-  name: "Conv_4"
-  type: "Convolution"
-  bottom: "onnx::Conv_87"
-  top: "input.19"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_5"
-  type: "ReLU"
-  bottom: "input.19"
-  top: "onnx::Conv_90"
-}
-layer {
-  name: "Conv_6"
-  type: "Convolution"
-  bottom: "onnx::Conv_90"
-  top: "input.27"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_7"
-  type: "ReLU"
-  bottom: "input.27"
-  top: "onnx::Conv_93"
-}
-layer {
-  name: "Conv_8"
-  type: "Convolution"
-  bottom: "onnx::Conv_93"
-  top: "input.35"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_9"
-  type: "ReLU"
-  bottom: "input.35"
-  top: "onnx::Conv_96"
-}
-layer {
-  name: "Conv_10"
-  type: "Convolution"
-  bottom: "onnx::Conv_96"
-  top: "input.43"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_11"
-  type: "ReLU"
-  bottom: "input.43"
-  top: "onnx::MaxPool_99"
-}
-layer {
-  name: "MaxPool_12"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_99"
-  top: "input.47"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_13"
-  type: "Convolution"
-  bottom: "input.47"
-  top: "input.55"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_14"
-  type: "ReLU"
-  bottom: "input.55"
-  top: "onnx::Conv_103"
-}
-layer {
-  name: "Conv_15"
-  type: "Convolution"
-  bottom: "onnx::Conv_103"
-  top: "input.63"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_16"
-  type: "ReLU"
-  bottom: "input.63"
-  top: "onnx::Conv_106"
-}
-layer {
-  name: "Conv_17"
-  type: "Convolution"
-  bottom: "onnx::Conv_106"
-  top: "input.71"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_18"
-  type: "ReLU"
-  bottom: "input.71"
-  top: "onnx::Conv_109"
-}
-layer {
-  name: "Conv_19"
-  type: "Convolution"
-  bottom: "onnx::Conv_109"
-  top: "input.79"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_20"
-  type: "ReLU"
-  bottom: "input.79"
-  top: "onnx::MaxPool_112"
-}
-layer {
-  name: "MaxPool_21"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_112"
-  top: "input.83"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_22"
-  type: "Convolution"
-  bottom: "input.83"
-  top: "input.91"
-  convolution_param {
-    num_output: 1024
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_23"
-  type: "ReLU"
-  bottom: "input.91"
-  top: "onnx::Conv_116"
-}
-layer {
-  name: "Conv_24"
-  type: "Convolution"
-  bottom: "onnx::Conv_116"
-  top: "input.99"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_25"
-  type: "ReLU"
-  bottom: "input.99"
-  top: "onnx::Conv_119"
-}
-layer {
-  name: "Conv_26"
-  type: "Convolution"
-  bottom: "onnx::Conv_119"
-  top: "input.107"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_27"
-  type: "ReLU"
-  bottom: "input.107"
-  top: "onnx::MaxPool_122"
-}
-layer {
-  name: "MaxPool_28"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_122"
-  top: "input.111"
-  pooling_param {
-    pool: MAX
-    kernel_h: 11
-    kernel_w: 11
-    stride_h: 11
-    stride_w: 11
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Reshape_29"
-  type: "Flatten"
-  bottom: "input.111"
-  top: "input.115"
-}
-layer {
-  name: "Gemm_30"
-  type: "InnerProduct"
-  bottom: "input.115"
-  top: "pred"
-  inner_product_param {
-    num_output: 1000
-    bias_term: true
-  }
-}
-
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.caffemodel b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.caffemodel
deleted file mode 100644
index 8c5ddc2..0000000
Binary files a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.caffemodel and /dev/null differ
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.prototxt b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.prototxt
deleted file mode 100644
index a1fd42b..0000000
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/1.5m/simv1_1.5m_m2.prototxt	
+++ /dev/null
@@ -1,387 +0,0 @@
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param {
-    shape {
-      dim: 1
-      dim: 3
-      dim: 224
-      dim: 224
-    }
-  }
-}
-layer {
-  name: "Conv_0"
-  type: "Convolution"
-  bottom: "data"
-  top: "input.3"
-  convolution_param {
-    num_output: 32
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_1"
-  type: "ReLU"
-  bottom: "input.3"
-  top: "onnx::Conv_84"
-}
-layer {
-  name: "Conv_2"
-  type: "Convolution"
-  bottom: "onnx::Conv_84"
-  top: "input.11"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_3"
-  type: "ReLU"
-  bottom: "input.11"
-  top: "onnx::Conv_87"
-}
-layer {
-  name: "Conv_4"
-  type: "Convolution"
-  bottom: "onnx::Conv_87"
-  top: "input.19"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_5"
-  type: "ReLU"
-  bottom: "input.19"
-  top: "onnx::Conv_90"
-}
-layer {
-  name: "Conv_6"
-  type: "Convolution"
-  bottom: "onnx::Conv_90"
-  top: "input.27"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_7"
-  type: "ReLU"
-  bottom: "input.27"
-  top: "onnx::Conv_93"
-}
-layer {
-  name: "Conv_8"
-  type: "Convolution"
-  bottom: "onnx::Conv_93"
-  top: "input.35"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_9"
-  type: "ReLU"
-  bottom: "input.35"
-  top: "onnx::Conv_96"
-}
-layer {
-  name: "Conv_10"
-  type: "Convolution"
-  bottom: "onnx::Conv_96"
-  top: "input.43"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_11"
-  type: "ReLU"
-  bottom: "input.43"
-  top: "onnx::MaxPool_99"
-}
-layer {
-  name: "MaxPool_12"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_99"
-  top: "input.47"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_13"
-  type: "Convolution"
-  bottom: "input.47"
-  top: "input.55"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_14"
-  type: "ReLU"
-  bottom: "input.55"
-  top: "onnx::Conv_103"
-}
-layer {
-  name: "Conv_15"
-  type: "Convolution"
-  bottom: "onnx::Conv_103"
-  top: "input.63"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_16"
-  type: "ReLU"
-  bottom: "input.63"
-  top: "onnx::Conv_106"
-}
-layer {
-  name: "Conv_17"
-  type: "Convolution"
-  bottom: "onnx::Conv_106"
-  top: "input.71"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_18"
-  type: "ReLU"
-  bottom: "input.71"
-  top: "onnx::Conv_109"
-}
-layer {
-  name: "Conv_19"
-  type: "Convolution"
-  bottom: "onnx::Conv_109"
-  top: "input.79"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_20"
-  type: "ReLU"
-  bottom: "input.79"
-  top: "onnx::MaxPool_112"
-}
-layer {
-  name: "MaxPool_21"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_112"
-  top: "input.83"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_22"
-  type: "Convolution"
-  bottom: "input.83"
-  top: "input.91"
-  convolution_param {
-    num_output: 1024
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_23"
-  type: "ReLU"
-  bottom: "input.91"
-  top: "onnx::Conv_116"
-}
-layer {
-  name: "Conv_24"
-  type: "Convolution"
-  bottom: "onnx::Conv_116"
-  top: "input.99"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_25"
-  type: "ReLU"
-  bottom: "input.99"
-  top: "onnx::Conv_119"
-}
-layer {
-  name: "Conv_26"
-  type: "Convolution"
-  bottom: "onnx::Conv_119"
-  top: "input.107"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_27"
-  type: "ReLU"
-  bottom: "input.107"
-  top: "onnx::MaxPool_122"
-}
-layer {
-  name: "MaxPool_28"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_122"
-  top: "input.111"
-  pooling_param {
-    pool: MAX
-    kernel_h: 11
-    kernel_w: 11
-    stride_h: 11
-    stride_w: 11
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Reshape_29"
-  type: "Flatten"
-  bottom: "input.111"
-  top: "input.115"
-}
-layer {
-  name: "Gemm_30"
-  type: "InnerProduct"
-  bottom: "input.115"
-  top: "pred"
-  inner_product_param {
-    num_output: 1000
-    bias_term: true
-  }
-}
-
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.caffemodel b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.caffemodel
deleted file mode 100644
index f19e008..0000000
Binary files a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.caffemodel and /dev/null differ
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.prototxt b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.prototxt
deleted file mode 100644
index 9957c96..0000000
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m1.prototxt	
+++ /dev/null
@@ -1,387 +0,0 @@
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param {
-    shape {
-      dim: 1
-      dim: 3
-      dim: 224
-      dim: 224
-    }
-  }
-}
-layer {
-  name: "Conv_0"
-  type: "Convolution"
-  bottom: "data"
-  top: "input.3"
-  convolution_param {
-    num_output: 48
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_1"
-  type: "ReLU"
-  bottom: "input.3"
-  top: "onnx::Conv_84"
-}
-layer {
-  name: "Conv_2"
-  type: "Convolution"
-  bottom: "onnx::Conv_84"
-  top: "input.11"
-  convolution_param {
-    num_output: 96
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_3"
-  type: "ReLU"
-  bottom: "input.11"
-  top: "onnx::Conv_87"
-}
-layer {
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-  type: "Convolution"
-  bottom: "onnx::Conv_87"
-  top: "input.19"
-  convolution_param {
-    num_output: 96
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
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-  top: "onnx::Conv_90"
-}
-layer {
-  name: "Conv_6"
-  type: "Convolution"
-  bottom: "onnx::Conv_90"
-  top: "input.27"
-  convolution_param {
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-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
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-  type: "ReLU"
-  bottom: "input.27"
-  top: "onnx::Conv_93"
-}
-layer {
-  name: "Conv_8"
-  type: "Convolution"
-  bottom: "onnx::Conv_93"
-  top: "input.35"
-  convolution_param {
-    num_output: 96
-    bias_term: true
-    group: 1
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-    kernel_w: 3
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-}
-layer {
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-  type: "ReLU"
-  bottom: "input.35"
-  top: "onnx::Conv_96"
-}
-layer {
-  name: "Conv_10"
-  type: "Convolution"
-  bottom: "onnx::Conv_96"
-  top: "input.43"
-  convolution_param {
-    num_output: 96
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-    group: 1
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-layer {
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-  type: "ReLU"
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-  top: "onnx::MaxPool_99"
-}
-layer {
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-  type: "Pooling"
-  bottom: "onnx::MaxPool_99"
-  top: "input.47"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
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-  type: "Convolution"
-  bottom: "input.47"
-  top: "input.55"
-  convolution_param {
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-layer {
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-layer {
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-  type: "Convolution"
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-  top: "input.63"
-  convolution_param {
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-    stride_w: 1
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-layer {
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-layer {
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-  bottom: "onnx::Conv_106"
-  top: "input.71"
-  convolution_param {
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-    stride_w: 1
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-layer {
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-  type: "ReLU"
-  bottom: "input.71"
-  top: "onnx::Conv_109"
-}
-layer {
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-  type: "Convolution"
-  bottom: "onnx::Conv_109"
-  top: "input.79"
-  convolution_param {
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-    group: 1
-    pad_h: 1
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-layer {
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-}
-layer {
-  name: "MaxPool_21"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_112"
-  top: "input.83"
-  pooling_param {
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-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
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-  bottom: "input.83"
-  top: "input.91"
-  convolution_param {
-    num_output: 1536
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-}
-layer {
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-  type: "ReLU"
-  bottom: "input.91"
-  top: "onnx::Conv_116"
-}
-layer {
-  name: "Conv_24"
-  type: "Convolution"
-  bottom: "onnx::Conv_116"
-  top: "input.99"
-  convolution_param {
-    num_output: 192
-    bias_term: true
-    group: 1
-    pad_h: 1
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-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_25"
-  type: "ReLU"
-  bottom: "input.99"
-  top: "onnx::Conv_119"
-}
-layer {
-  name: "Conv_26"
-  type: "Convolution"
-  bottom: "onnx::Conv_119"
-  top: "input.107"
-  convolution_param {
-    num_output: 192
-    bias_term: true
-    group: 1
-    pad_h: 1
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-    kernel_h: 3
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-layer {
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-  type: "ReLU"
-  bottom: "input.107"
-  top: "onnx::MaxPool_122"
-}
-layer {
-  name: "MaxPool_28"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_122"
-  top: "input.111"
-  pooling_param {
-    pool: MAX
-    kernel_h: 11
-    kernel_w: 11
-    stride_h: 11
-    stride_w: 11
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Reshape_29"
-  type: "Flatten"
-  bottom: "input.111"
-  top: "input.115"
-}
-layer {
-  name: "Gemm_30"
-  type: "InnerProduct"
-  bottom: "input.115"
-  top: "pred"
-  inner_product_param {
-    num_output: 1000
-    bias_term: true
-  }
-}
-
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.caffemodel b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.caffemodel
deleted file mode 100644
index 3134cb5..0000000
Binary files a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.caffemodel and /dev/null differ
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.prototxt b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.prototxt
deleted file mode 100644
index 225407b..0000000
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/3m/simv1_3m_m2.prototxt	
+++ /dev/null
@@ -1,387 +0,0 @@
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param {
-    shape {
-      dim: 1
-      dim: 3
-      dim: 224
-      dim: 224
-    }
-  }
-}
-layer {
-  name: "Conv_0"
-  type: "Convolution"
-  bottom: "data"
-  top: "input.3"
-  convolution_param {
-    num_output: 48
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_1"
-  type: "ReLU"
-  bottom: "input.3"
-  top: "onnx::Conv_84"
-}
-layer {
-  name: "Conv_2"
-  type: "Convolution"
-  bottom: "onnx::Conv_84"
-  top: "input.11"
-  convolution_param {
-    num_output: 96
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_3"
-  type: "ReLU"
-  bottom: "input.11"
-  top: "onnx::Conv_87"
-}
-layer {
-  name: "Conv_4"
-  type: "Convolution"
-  bottom: "onnx::Conv_87"
-  top: "input.19"
-  convolution_param {
-    num_output: 96
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
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-}
-layer {
-  name: "Relu_5"
-  type: "ReLU"
-  bottom: "input.19"
-  top: "onnx::Conv_90"
-}
-layer {
-  name: "Conv_6"
-  type: "Convolution"
-  bottom: "onnx::Conv_90"
-  top: "input.27"
-  convolution_param {
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-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_7"
-  type: "ReLU"
-  bottom: "input.27"
-  top: "onnx::Conv_93"
-}
-layer {
-  name: "Conv_8"
-  type: "Convolution"
-  bottom: "onnx::Conv_93"
-  top: "input.35"
-  convolution_param {
-    num_output: 96
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-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
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-layer {
-  name: "Relu_9"
-  type: "ReLU"
-  bottom: "input.35"
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-}
-layer {
-  name: "Conv_10"
-  type: "Convolution"
-  bottom: "onnx::Conv_96"
-  top: "input.43"
-  convolution_param {
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-  bottom: "input.43"
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-layer {
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-  bottom: "onnx::MaxPool_99"
-  top: "input.47"
-  pooling_param {
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-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
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-  bottom: "input.47"
-  top: "input.55"
-  convolution_param {
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-    bias_term: true
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-    pad_h: 1
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-layer {
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-  top: "onnx::Conv_103"
-}
-layer {
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-  bottom: "onnx::Conv_103"
-  top: "input.63"
-  convolution_param {
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-    kernel_w: 3
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-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
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-  top: "onnx::Conv_106"
-}
-layer {
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-  type: "Convolution"
-  bottom: "onnx::Conv_106"
-  top: "input.71"
-  convolution_param {
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-    stride_h: 1
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-}
-layer {
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-  type: "ReLU"
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-  top: "onnx::Conv_109"
-}
-layer {
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-  type: "Convolution"
-  bottom: "onnx::Conv_109"
-  top: "input.79"
-  convolution_param {
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-}
-layer {
-  name: "Relu_20"
-  type: "ReLU"
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-  top: "onnx::MaxPool_112"
-}
-layer {
-  name: "MaxPool_21"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_112"
-  top: "input.83"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_22"
-  type: "Convolution"
-  bottom: "input.83"
-  top: "input.91"
-  convolution_param {
-    num_output: 1536
-    bias_term: true
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-    pad_h: 1
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-}
-layer {
-  name: "Relu_23"
-  type: "ReLU"
-  bottom: "input.91"
-  top: "onnx::Conv_116"
-}
-layer {
-  name: "Conv_24"
-  type: "Convolution"
-  bottom: "onnx::Conv_116"
-  top: "input.99"
-  convolution_param {
-    num_output: 192
-    bias_term: true
-    group: 1
-    pad_h: 1
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-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
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-}
-layer {
-  name: "Relu_25"
-  type: "ReLU"
-  bottom: "input.99"
-  top: "onnx::Conv_119"
-}
-layer {
-  name: "Conv_26"
-  type: "Convolution"
-  bottom: "onnx::Conv_119"
-  top: "input.107"
-  convolution_param {
-    num_output: 192
-    bias_term: true
-    group: 1
-    pad_h: 1
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-    kernel_h: 3
-    kernel_w: 3
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-}
-layer {
-  name: "Relu_27"
-  type: "ReLU"
-  bottom: "input.107"
-  top: "onnx::MaxPool_122"
-}
-layer {
-  name: "MaxPool_28"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_122"
-  top: "input.111"
-  pooling_param {
-    pool: MAX
-    kernel_h: 11
-    kernel_w: 11
-    stride_h: 11
-    stride_w: 11
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Reshape_29"
-  type: "Flatten"
-  bottom: "input.111"
-  top: "input.115"
-}
-layer {
-  name: "Gemm_30"
-  type: "InnerProduct"
-  bottom: "input.115"
-  top: "pred"
-  inner_product_param {
-    num_output: 1000
-    bias_term: true
-  }
-}
-
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.caffemodel b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.caffemodel
deleted file mode 100644
index 507a985..0000000
Binary files a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.caffemodel and /dev/null differ
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.prototxt b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.prototxt
deleted file mode 100644
index e5e0581..0000000
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/5m/simv1_5m_m2.prototxt	
+++ /dev/null
@@ -1,387 +0,0 @@
-layer {
-  name: "data"
-  type: "Input"
-  top: "data"
-  input_param {
-    shape {
-      dim: 1
-      dim: 3
-      dim: 224
-      dim: 224
-    }
-  }
-}
-layer {
-  name: "Conv_0"
-  type: "Convolution"
-  bottom: "data"
-  top: "input.3"
-  convolution_param {
-    num_output: 64
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_1"
-  type: "ReLU"
-  bottom: "input.3"
-  top: "onnx::Conv_84"
-}
-layer {
-  name: "Conv_2"
-  type: "Convolution"
-  bottom: "onnx::Conv_84"
-  top: "input.11"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_3"
-  type: "ReLU"
-  bottom: "input.11"
-  top: "onnx::Conv_87"
-}
-layer {
-  name: "Conv_4"
-  type: "Convolution"
-  bottom: "onnx::Conv_87"
-  top: "input.19"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_5"
-  type: "ReLU"
-  bottom: "input.19"
-  top: "onnx::Conv_90"
-}
-layer {
-  name: "Conv_6"
-  type: "Convolution"
-  bottom: "onnx::Conv_90"
-  top: "input.27"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 2
-    stride_w: 2
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_7"
-  type: "ReLU"
-  bottom: "input.27"
-  top: "onnx::Conv_93"
-}
-layer {
-  name: "Conv_8"
-  type: "Convolution"
-  bottom: "onnx::Conv_93"
-  top: "input.35"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_9"
-  type: "ReLU"
-  bottom: "input.35"
-  top: "onnx::Conv_96"
-}
-layer {
-  name: "Conv_10"
-  type: "Convolution"
-  bottom: "onnx::Conv_96"
-  top: "input.43"
-  convolution_param {
-    num_output: 128
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_11"
-  type: "ReLU"
-  bottom: "input.43"
-  top: "onnx::MaxPool_99"
-}
-layer {
-  name: "MaxPool_12"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_99"
-  top: "input.47"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_13"
-  type: "Convolution"
-  bottom: "input.47"
-  top: "input.55"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_14"
-  type: "ReLU"
-  bottom: "input.55"
-  top: "onnx::Conv_103"
-}
-layer {
-  name: "Conv_15"
-  type: "Convolution"
-  bottom: "onnx::Conv_103"
-  top: "input.63"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_16"
-  type: "ReLU"
-  bottom: "input.63"
-  top: "onnx::Conv_106"
-}
-layer {
-  name: "Conv_17"
-  type: "Convolution"
-  bottom: "onnx::Conv_106"
-  top: "input.71"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_18"
-  type: "ReLU"
-  bottom: "input.71"
-  top: "onnx::Conv_109"
-}
-layer {
-  name: "Conv_19"
-  type: "Convolution"
-  bottom: "onnx::Conv_109"
-  top: "input.79"
-  convolution_param {
-    num_output: 512
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_20"
-  type: "ReLU"
-  bottom: "input.79"
-  top: "onnx::MaxPool_112"
-}
-layer {
-  name: "MaxPool_21"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_112"
-  top: "input.83"
-  pooling_param {
-    pool: MAX
-    kernel_h: 2
-    kernel_w: 2
-    stride_h: 2
-    stride_w: 2
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Conv_22"
-  type: "Convolution"
-  bottom: "input.83"
-  top: "input.91"
-  convolution_param {
-    num_output: 2048
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_23"
-  type: "ReLU"
-  bottom: "input.91"
-  top: "onnx::Conv_116"
-}
-layer {
-  name: "Conv_24"
-  type: "Convolution"
-  bottom: "onnx::Conv_116"
-  top: "input.99"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 1
-    kernel_w: 1
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_25"
-  type: "ReLU"
-  bottom: "input.99"
-  top: "onnx::Conv_119"
-}
-layer {
-  name: "Conv_26"
-  type: "Convolution"
-  bottom: "onnx::Conv_119"
-  top: "input.107"
-  convolution_param {
-    num_output: 256
-    bias_term: true
-    group: 1
-    pad_h: 1
-    pad_w: 1
-    kernel_h: 3
-    kernel_w: 3
-    stride_h: 1
-    stride_w: 1
-    dilation: 1
-  }
-}
-layer {
-  name: "Relu_27"
-  type: "ReLU"
-  bottom: "input.107"
-  top: "onnx::MaxPool_122"
-}
-layer {
-  name: "MaxPool_28"
-  type: "Pooling"
-  bottom: "onnx::MaxPool_122"
-  top: "input.111"
-  pooling_param {
-    pool: MAX
-    kernel_h: 11
-    kernel_w: 11
-    stride_h: 11
-    stride_w: 11
-    pad_h: 0
-    pad_w: 0
-  }
-}
-layer {
-  name: "Reshape_29"
-  type: "Flatten"
-  bottom: "input.111"
-  top: "input.115"
-}
-layer {
-  name: "Gemm_30"
-  type: "InnerProduct"
-  bottom: "input.115"
-  top: "pred"
-  inner_product_param {
-    num_output: 1000
-    bias_term: true
-  }
-}
-
diff --git a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/readme.md b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/readme.md
index 1ea7825..b958cd0 100644
--- a/SimpNet_V1/Benchmarks Results with Models/IMAGENET/readme.md	
+++ b/SimpNet_V1/Benchmarks Results with Models/IMAGENET/readme.md	
@@ -1,4 +1,8 @@
 
+### Where are the pretrained weights?
+All pretrained weights are now accessible from [Release section](https://github.com/Coderx7/SimpleNet/releases) of the reposityory.
+
+### Note
 Please note that models are converted from onnx to caffe.
 The mean, std and crop ratio used are as follows: 
 ```python