keras報錯:Cannot clone object <keras.wrappers.scikit_learn.KerasClassifier object at 0x000001300883B848>
阿新 • • 發佈:2020-11-04
這是一個自動調整超引數的功能演示,
首先該程式有一個bug,可能在經過很長一段時間的訓練之後,最後一步報錯了,
Traceback (most recent call last): File "mnist_sklearn_wrapper.py", line 96, in <module> validator.fit(x_train, y_train) File "C:\ProgramData\Miniconda3\lib\site-packages\sklearn\model_selection\_search.py", line 736, in fit **self.best_params_)) File "C:\ProgramData\Miniconda3\lib\site-packages\sklearn\base.py", line 82, in clone (estimator, name)) RuntimeError: Cannot clone object <keras.wrappers.scikit_learn.KerasClassifier object at 0x000001300883B848>, as the constructor either does not set or modifies parameter dense_layer_sizes
我看官方有人提交了一個pull request,
https://github.com/keras-team/keras/pull/13598/commits/c735ab5b89bbf935075c84aab3437468e1fe8245
修改後可以正常執行,但該修改的整合測試卻沒有通過,所以可能不算是一個完美修復
不過可以臨時按照它的方式進行修改,在測試完後再改回來
GridSearchCV 提供了幾組候選引數,
len(dense_layer_sizes)=4
len(epochs)=2
len(filters)=1
len(kernel_size)=1
len(pool_size)=1
排列組合一下,總共是4*2*1*1*1,總共八種情況,也就是說可以組成 8 種神經網路訓練方式,來比較一下,哪種排列組合的訓練效果是最好的;每種訓練方式會重複五次,也就是總共會訓練 40 次;
下面附完整訓練日誌:
Using TensorFlow backend. 2020-04-03 14:52:24.644605: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 2020-04-03 14:52:27.891345: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll 2020-04-03 14:52:28.988239: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: pciBusID: 0000:01:00.0 name: Quadro RTX 3000 computeCapability: 7.5 coreClock: 1.38GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s 2020-04-03 14:52:28.994920: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll 2020-04-03 14:52:29.003690: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll 2020-04-03 14:52:29.013001: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll 2020-04-03 14:52:29.018018: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll 2020-04-03 14:52:29.025735: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll 2020-04-03 14:52:29.034548: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll 2020-04-03 14:52:29.047961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll 2020-04-03 14:52:29.052178: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0 2020-04-03 14:52:29.054762: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 2020-04-03 14:52:29.067432: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties: pciBusID: 0000:01:00.0 name: Quadro RTX 3000 computeCapability: 7.5 coreClock: 1.38GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s 2020-04-03 14:52:29.074938: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll 2020-04-03 14:52:29.080278: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll 2020-04-03 14:52:29.082466: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll 2020-04-03 14:52:29.085739: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll 2020-04-03 14:52:29.089171: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll 2020-04-03 14:52:29.091364: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll 2020-04-03 14:52:29.095283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll 2020-04-03 14:52:29.097662: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0 2020-04-03 14:52:29.638757: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix: 2020-04-03 14:52:29.642200: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0 2020-04-03 14:52:29.644956: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N 2020-04-03 14:52:29.647308: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4604 MB memory) -> physical GPU (device: 0, name: Quadro RTX 3000, pci bus id: 0000:01:00.0, compute capability: 7.5) Model: "sequential_1" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_1 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_1 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_2 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_2 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_1 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_1 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_1 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_1 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_3 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_2 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_2 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_4 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 2020-04-03 14:52:30.684354: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll 2020-04-03 14:52:30.950919: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll 2020-04-03 14:52:32.029379: W tensorflow/stream_executor/gpu/redzone_allocator.cc:312] Internal: Invoking GPU asm compilation is supported on Cuda non-Windows platforms only Relying on driver to perform ptx compilation. This message will be only logged once. 48000/48000 [==============================] - 6s 135us/step - loss: 0.6358 - accuracy: 0.7876 Epoch 2/3 48000/48000 [==============================] - 5s 100us/step - loss: 0.3572 - accuracy: 0.8862 Epoch 3/3 48000/48000 [==============================] - 5s 100us/step - loss: 0.2977 - accuracy: 0.9071 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_2" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_3 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_5 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_4 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_6 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_2 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_3 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_2 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_3 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_7 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_4 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_4 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_8 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.6602 - accuracy: 0.7871 Epoch 2/3 48000/48000 [==============================] - 5s 101us/step - loss: 0.3518 - accuracy: 0.8912 Epoch 3/3 48000/48000 [==============================] - 5s 100us/step - loss: 0.2985 - accuracy: 0.9089 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_3" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_5 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_9 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_6 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_10 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_3 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_5 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_3 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_5 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_11 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_6 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_6 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_12 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 96us/step - loss: 0.6220 - accuracy: 0.7967 Epoch 2/3 48000/48000 [==============================] - 5s 101us/step - loss: 0.3455 - accuracy: 0.8933 Epoch 3/3 48000/48000 [==============================] - 4s 93us/step - loss: 0.2835 - accuracy: 0.9113 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_4" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_7 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_13 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_8 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_14 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_4 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_7 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_4 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_7 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_15 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_8 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_8 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_16 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 108us/step - loss: 0.6077 - accuracy: 0.8029 Epoch 2/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.3222 - accuracy: 0.9013 Epoch 3/3 48000/48000 [==============================] - 5s 101us/step - loss: 0.2716 - accuracy: 0.9163 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_5" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_9 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_17 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_10 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_18 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_5 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_9 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_5 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_9 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_19 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_10 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_10 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_20 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 96us/step - loss: 0.5510 - accuracy: 0.8200 Epoch 2/3 48000/48000 [==============================] - 5s 101us/step - loss: 0.3218 - accuracy: 0.8961 Epoch 3/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.2708 - accuracy: 0.9138 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_6" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_11 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_21 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_12 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_22 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_6 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_11 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_6 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_11 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_23 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_12 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_12 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_24 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.6296 - accuracy: 0.7956 Epoch 2/6 48000/48000 [==============================] - 4s 93us/step - loss: 0.3656 - accuracy: 0.8840 Epoch 3/6 48000/48000 [==============================] - 5s 95us/step - loss: 0.3040 - accuracy: 0.9047 Epoch 4/6 48000/48000 [==============================] - 5s 94us/step - loss: 0.2726 - accuracy: 0.9158 Epoch 5/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.2573 - accuracy: 0.9214 Epoch 6/6 48000/48000 [==============================] - 4s 93us/step - loss: 0.2341 - accuracy: 0.9281 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_7" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_13 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_25 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_14 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_26 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_7 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_13 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_7 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_13 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_27 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_14 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_14 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_28 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.6525 - accuracy: 0.7845 Epoch 2/6 48000/48000 [==============================] - 5s 104us/step - loss: 0.3825 - accuracy: 0.8804 Epoch 3/6 48000/48000 [==============================] - 5s 106us/step - loss: 0.3172 - accuracy: 0.9012 Epoch 4/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.2687 - accuracy: 0.9178 Epoch 5/6 48000/48000 [==============================] - 5s 99us/step - loss: 0.2373 - accuracy: 0.9275 Epoch 6/6 48000/48000 [==============================] - 5s 101us/step - loss: 0.2251 - accuracy: 0.9293 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_8" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_15 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_29 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_16 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_30 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_8 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_15 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_8 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_15 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_31 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_16 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_16 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_32 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 99us/step - loss: 0.5917 - accuracy: 0.8095 Epoch 2/6 48000/48000 [==============================] - 4s 89us/step - loss: 0.3464 - accuracy: 0.8930 Epoch 3/6 48000/48000 [==============================] - 5s 95us/step - loss: 0.3023 - accuracy: 0.9087 Epoch 4/6 48000/48000 [==============================] - 4s 89us/step - loss: 0.2709 - accuracy: 0.9164 Epoch 5/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.2518 - accuracy: 0.9237 Epoch 6/6 48000/48000 [==============================] - 4s 90us/step - loss: 0.2447 - accuracy: 0.9250 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_9" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_17 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_33 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_18 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_34 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_9 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_17 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_9 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_17 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_35 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_18 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_18 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_36 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 98us/step - loss: 0.5954 - accuracy: 0.8045 Epoch 2/6 48000/48000 [==============================] - 4s 93us/step - loss: 0.3322 - accuracy: 0.8965 Epoch 3/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.2954 - accuracy: 0.9091 Epoch 4/6 48000/48000 [==============================] - 5s 96us/step - loss: 0.2624 - accuracy: 0.9190 Epoch 5/6 48000/48000 [==============================] - 5s 101us/step - loss: 0.2439 - accuracy: 0.9249 Epoch 6/6 48000/48000 [==============================] - 5s 98us/step - loss: 0.2308 - accuracy: 0.9290 dense_layer_sizes [32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_10" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_19 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_37 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_20 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_38 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_10 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_19 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_10 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_19 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_39 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_20 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_20 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_40 (Activation) (None, 10) 0 ================================================================================ Total params: 37,890 Trainable params: 37,890 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 104us/step - loss: 0.5412 - accuracy: 0.8263 Epoch 2/6 48000/48000 [==============================] - 4s 94us/step - loss: 0.3317 - accuracy: 0.8970 Epoch 3/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.2831 - accuracy: 0.9139 Epoch 4/6 48000/48000 [==============================] - 5s 94us/step - loss: 0.2618 - accuracy: 0.9202 Epoch 5/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.2422 - accuracy: 0.9269 Epoch 6/6 48000/48000 [==============================] - 5s 95us/step - loss: 0.2302 - accuracy: 0.9302 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_11" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_21 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_41 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_22 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_42 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_11 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_21 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_11 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_21 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_43 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_22 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_22 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_44 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 102us/step - loss: 0.4149 - accuracy: 0.8740 Epoch 2/3 48000/48000 [==============================] - 5s 96us/step - loss: 0.2064 - accuracy: 0.9419 Epoch 3/3 48000/48000 [==============================] - 4s 92us/step - loss: 0.1668 - accuracy: 0.9507 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_12" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_23 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_45 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_24 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_46 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_12 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_23 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_12 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_23 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_47 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_24 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_24 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_48 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 96us/step - loss: 0.4150 - accuracy: 0.8691 Epoch 2/3 48000/48000 [==============================] - 5s 95us/step - loss: 0.1982 - accuracy: 0.9417 Epoch 3/3 48000/48000 [==============================] - 4s 93us/step - loss: 0.1593 - accuracy: 0.9532 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_13" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_25 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_49 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_26 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_50 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_13 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_25 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_13 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_25 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_51 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_26 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_26 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_52 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 100us/step - loss: 0.4597 - accuracy: 0.8565 Epoch 2/3 48000/48000 [==============================] - 4s 90us/step - loss: 0.2266 - accuracy: 0.9339 Epoch 3/3 48000/48000 [==============================] - 4s 93us/step - loss: 0.1774 - accuracy: 0.9489 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_14" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_27 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_53 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_28 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_54 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_14 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_27 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_14 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_27 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_55 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_28 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_28 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_56 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 96us/step - loss: 0.4102 - accuracy: 0.8733 Epoch 2/3 48000/48000 [==============================] - 4s 93us/step - loss: 0.2006 - accuracy: 0.9402 Epoch 3/3 48000/48000 [==============================] - 5s 94us/step - loss: 0.1643 - accuracy: 0.9522 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_15" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_29 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_57 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_30 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_58 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_15 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_29 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_15 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_29 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_59 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_30 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_30 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_60 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 108us/step - loss: 0.4029 - accuracy: 0.8747 Epoch 2/3 48000/48000 [==============================] - 5s 98us/step - loss: 0.2007 - accuracy: 0.9412 Epoch 3/3 48000/48000 [==============================] - 5s 97us/step - loss: 0.1701 - accuracy: 0.9515 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_16" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_31 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_61 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_32 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_62 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_16 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_31 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_16 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_31 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_63 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_32 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_32 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_64 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 97us/step - loss: 0.4400 - accuracy: 0.8624 Epoch 2/6 48000/48000 [==============================] - 5s 97us/step - loss: 0.2095 - accuracy: 0.9378 Epoch 3/6 48000/48000 [==============================] - 5s 95us/step - loss: 0.1630 - accuracy: 0.9518 Epoch 4/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.1401 - accuracy: 0.9592 Epoch 5/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.1276 - accuracy: 0.9625 Epoch 6/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.1227 - accuracy: 0.9652 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_17" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_33 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_65 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_34 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_66 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_17 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_33 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_17 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_33 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_67 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_34 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_34 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_68 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 101us/step - loss: 0.4304 - accuracy: 0.8656 Epoch 2/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.2009 - accuracy: 0.9404 Epoch 3/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.1646 - accuracy: 0.9520 Epoch 4/6 48000/48000 [==============================] - 5s 97us/step - loss: 0.1440 - accuracy: 0.9594 Epoch 5/6 48000/48000 [==============================] - 5s 100us/step - loss: 0.1280 - accuracy: 0.9622 Epoch 6/6 48000/48000 [==============================] - 5s 100us/step - loss: 0.1211 - accuracy: 0.9660 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_18" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_35 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_69 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_36 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_70 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_18 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_35 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_18 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_35 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_71 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_36 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_36 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_72 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 96us/step - loss: 0.4330 - accuracy: 0.8669 Epoch 2/6 48000/48000 [==============================] - 5s 94us/step - loss: 0.2064 - accuracy: 0.9399 Epoch 3/6 48000/48000 [==============================] - 5s 95us/step - loss: 0.1694 - accuracy: 0.9508 Epoch 4/6 48000/48000 [==============================] - 4s 92us/step - loss: 0.1491 - accuracy: 0.9570 Epoch 5/6 48000/48000 [==============================] - 4s 91us/step - loss: 0.1370 - accuracy: 0.9597 Epoch 6/6 48000/48000 [==============================] - 4s 90us/step - loss: 0.1308 - accuracy: 0.9616 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_19" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_37 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_73 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_38 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_74 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_19 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_37 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_19 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_37 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_75 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_38 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_38 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_76 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.4040 - accuracy: 0.8748 Epoch 2/6 48000/48000 [==============================] - 5s 97us/step - loss: 0.2013 - accuracy: 0.9425 Epoch 3/6 48000/48000 [==============================] - 4s 93us/step - loss: 0.1621 - accuracy: 0.9540 Epoch 4/6 48000/48000 [==============================] - 4s 90us/step - loss: 0.1413 - accuracy: 0.9591 Epoch 5/6 48000/48000 [==============================] - 4s 90us/step - loss: 0.1298 - accuracy: 0.9629 Epoch 6/6 48000/48000 [==============================] - 4s 89us/step - loss: 0.1214 - accuracy: 0.9652 dense_layer_sizes [64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_20" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_39 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_77 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_40 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_78 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_20 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_39 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_20 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_39 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_79 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_40 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_40 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_80 (Activation) (None, 10) 0 ================================================================================ Total params: 75,106 Trainable params: 75,106 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 112us/step - loss: 0.4608 - accuracy: 0.8560 Epoch 2/6 48000/48000 [==============================] - 6s 127us/step - loss: 0.2183 - accuracy: 0.9352 Epoch 3/6 48000/48000 [==============================] - 5s 111us/step - loss: 0.1730 - accuracy: 0.9483 Epoch 4/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.1475 - accuracy: 0.9566 Epoch 5/6 48000/48000 [==============================] - 5s 98us/step - loss: 0.1427 - accuracy: 0.9582 Epoch 6/6 48000/48000 [==============================] - 6s 122us/step - loss: 0.1321 - accuracy: 0.9610 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_21" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_41 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_81 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_42 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_82 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_21 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_41 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_21 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_41 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_83 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_42 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_84 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_42 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_43 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_85 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 7s 144us/step - loss: 0.5166 - accuracy: 0.8412 Epoch 2/3 48000/48000 [==============================] - 6s 129us/step - loss: 0.2497 - accuracy: 0.9309 Epoch 3/3 48000/48000 [==============================] - 7s 147us/step - loss: 0.2095 - accuracy: 0.9419 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_22" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_43 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_86 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_44 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_87 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_22 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_43 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_22 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_44 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_88 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_45 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_89 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_44 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_46 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_90 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 6s 135us/step - loss: 0.5476 - accuracy: 0.8271 Epoch 2/3 48000/48000 [==============================] - 8s 168us/step - loss: 0.2757 - accuracy: 0.9202 Epoch 3/3 48000/48000 [==============================] - 5s 102us/step - loss: 0.2231 - accuracy: 0.9364 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_23" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_45 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_91 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_46 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_92 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_23 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_45 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_23 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_47 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_93 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_48 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_94 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_46 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_49 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_95 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 111us/step - loss: 0.5845 - accuracy: 0.8112 Epoch 2/3 48000/48000 [==============================] - 6s 115us/step - loss: 0.2841 - accuracy: 0.9131 Epoch 3/3 48000/48000 [==============================] - 5s 110us/step - loss: 0.2219 - accuracy: 0.9337 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_24" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_47 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_96 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_48 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_97 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_24 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_47 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_24 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_50 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_98 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_51 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_99 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_48 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_52 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_100 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 6s 116us/step - loss: 0.5443 - accuracy: 0.8274 Epoch 2/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.2653 - accuracy: 0.9233 Epoch 3/3 48000/48000 [==============================] - 6s 115us/step - loss: 0.2106 - accuracy: 0.9409 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_25" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_49 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_101 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_50 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_102 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_25 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_49 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_25 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_53 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_103 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_54 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_104 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_50 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_55 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_105 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 114us/step - loss: 0.4992 - accuracy: 0.8474 Epoch 2/3 48000/48000 [==============================] - 5s 111us/step - loss: 0.2467 - accuracy: 0.9303 Epoch 3/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.2019 - accuracy: 0.9448 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_26" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_51 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_106 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_52 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_107 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_26 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_51 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_26 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_56 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_108 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_57 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_109 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_52 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_58 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_110 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 6s 120us/step - loss: 0.5868 - accuracy: 0.8106 Epoch 2/6 48000/48000 [==============================] - 5s 110us/step - loss: 0.3112 - accuracy: 0.9080 Epoch 3/6 48000/48000 [==============================] - 5s 107us/step - loss: 0.2556 - accuracy: 0.9232 Epoch 4/6 48000/48000 [==============================] - 5s 111us/step - loss: 0.2219 - accuracy: 0.9328 Epoch 5/6 48000/48000 [==============================] - 5s 111us/step - loss: 0.2053 - accuracy: 0.9393 Epoch 6/6 48000/48000 [==============================] - 6s 115us/step - loss: 0.1884 - accuracy: 0.9440 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_27" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_53 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_111 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_54 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_112 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_27 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_53 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_27 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_59 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_113 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_60 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_114 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_54 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_61 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_115 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 6s 126us/step - loss: 0.5026 - accuracy: 0.8442 Epoch 2/6 48000/48000 [==============================] - 6s 120us/step - loss: 0.2589 - accuracy: 0.9266 Epoch 3/6 48000/48000 [==============================] - 5s 111us/step - loss: 0.2069 - accuracy: 0.9421 Epoch 4/6 48000/48000 [==============================] - 5s 112us/step - loss: 0.1845 - accuracy: 0.9492 Epoch 5/6 48000/48000 [==============================] - 6s 132us/step - loss: 0.1676 - accuracy: 0.9548 Epoch 6/6 48000/48000 [==============================] - 5s 112us/step - loss: 0.1561 - accuracy: 0.9570 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_28" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_55 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_116 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_56 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_117 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_28 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_55 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_28 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_62 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_118 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_63 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_119 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_56 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_64 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_120 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 7s 150us/step - loss: 0.5850 - accuracy: 0.8099 Epoch 2/6 48000/48000 [==============================] - 5s 112us/step - loss: 0.2859 - accuracy: 0.9157 Epoch 3/6 48000/48000 [==============================] - 7s 142us/step - loss: 0.2297 - accuracy: 0.9351 Epoch 4/6 48000/48000 [==============================] - 7s 154us/step - loss: 0.1945 - accuracy: 0.9457 Epoch 5/6 48000/48000 [==============================] - 7s 144us/step - loss: 0.1696 - accuracy: 0.9522 Epoch 6/6 48000/48000 [==============================] - 5s 111us/step - loss: 0.1580 - accuracy: 0.9556 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_29" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_57 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_121 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_58 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_122 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_29 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_57 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_29 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_65 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_123 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_66 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_124 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_58 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_67 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_125 (Activation) (None, 10) 0 ==========================================================#61;====================== Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 6s 121us/step - loss: 0.5203 - accuracy: 0.8362 Epoch 2/6 48000/48000 [==============================] - 5s 110us/step - loss: 0.2587 - accuracy: 0.9243 Epoch 3/6 48000/48000 [==============================] - 5s 106us/step - loss: 0.2045 - accuracy: 0.9410 Epoch 4/6 48000/48000 [==============================] - 5s 104us/step - loss: 0.1789 - accuracy: 0.9501 Epoch 5/6 48000/48000 [==============================] - 5s 108us/step - loss: 0.1637 - accuracy: 0.9555 Epoch 6/6 48000/48000 [==============================] - 5s 106us/step - loss: 0.1535 - accuracy: 0.9581 dense_layer_sizes [32, 32] filters 8 kernel_size 3 pool_size 2 Model: "sequential_30" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_59 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_126 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_60 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_127 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_30 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_59 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_30 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_68 (Dense) (None, 32) 36896 ________________________________________________________________________________ activation_128 (Activation) (None, 32) 0 ________________________________________________________________________________ dense_69 (Dense) (None, 32) 1056 ________________________________________________________________________________ activation_129 (Activation) (None, 32) 0 ________________________________________________________________________________ dropout_60 (Dropout) (None, 32) 0 ________________________________________________________________________________ dense_70 (Dense) (None, 10) 330 ________________________________________________________________________________ activation_130 (Activation) (None, 10) 0 ================================================================================ Total params: 38,946 Trainable params: 38,946 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 108us/step - loss: 0.6101 - accuracy: 0.8081 Epoch 2/6 48000/48000 [==============================] - 5s 110us/step - loss: 0.2820 - accuracy: 0.9218 Epoch 3/6 48000/48000 [==============================] - 6s 124us/step - loss: 0.2187 - accuracy: 0.9398 Epoch 4/6 48000/48000 [==============================] - 5s 108us/step - loss: 0.1816 - accuracy: 0.9501 Epoch 5/6 48000/48000 [==============================] - 5s 114us/step - loss: 0.1606 - accuracy: 0.9565 Epoch 6/6 48000/48000 [==============================] - 5s 107us/step - loss: 0.1487 - accuracy: 0.9589 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_31" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_61 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_131 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_62 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_132 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_31 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_61 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_31 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_71 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_133 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_72 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_134 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_62 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_73 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_135 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 6s 115us/step - loss: 0.3673 - accuracy: 0.8900 Epoch 2/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.1600 - accuracy: 0.9555 Epoch 3/3 48000/48000 [==============================] - 5s 107us/step - loss: 0.1213 - accuracy: 0.9665 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_32" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_63 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_136 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_64 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_137 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_32 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_63 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_32 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_74 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_138 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_75 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_139 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_64 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_76 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_140 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 110us/step - loss: 0.3320 - accuracy: 0.8991 Epoch 2/3 48000/48000 [==============================] - 5s 108us/step - loss: 0.1442 - accuracy: 0.9607 Epoch 3/3 48000/48000 [==============================] - 5s 103us/step - loss: 0.1134 - accuracy: 0.9695 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_33" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_65 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_141 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_66 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_142 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_33 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_65 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_33 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_77 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_143 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_78 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_144 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_66 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_79 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_145 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 6s 118us/step - loss: 0.3735 - accuracy: 0.8865 Epoch 2/3 48000/48000 [==============================] - 5s 109us/step - loss: 0.1466 - accuracy: 0.9615 Epoch 3/3 48000/48000 [==============================] - 6s 117us/step - loss: 0.1154 - accuracy: 0.9688 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_34" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_67 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_146 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_68 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_147 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_34 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_67 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_34 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_80 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_148 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_81 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_149 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_68 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_82 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_150 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 105us/step - loss: 0.3600 - accuracy: 0.8920 Epoch 2/3 48000/48000 [==============================] - 5s 100us/step - loss: 0.1543 - accuracy: 0.9586 Epoch 3/3 48000/48000 [==============================] - 5s 106us/step - loss: 0.1130 - accuracy: 0.9692 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_35" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_69 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_151 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_70 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_152 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_35 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_69 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_35 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_83 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_153 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_84 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_154 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_70 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_85 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_155 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/3 48000/48000 [==============================] - 5s 113us/step - loss: 0.3310 - accuracy: 0.9006 Epoch 2/3 48000/48000 [==============================] - 5s 104us/step - loss: 0.1388 - accuracy: 0.9621 Epoch 3/3 48000/48000 [==============================] - 5s 106us/step - loss: 0.1067 - accuracy: 0.9707 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_36" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_71 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_156 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_72 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_157 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_36 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_71 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_36 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_86 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_158 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_87 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_159 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_72 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_88 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_160 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 108us/step - loss: 0.3465 - accuracy: 0.8963 Epoch 2/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.1464 - accuracy: 0.9599 Epoch 3/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.1106 - accuracy: 0.9700 Epoch 4/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.0940 - accuracy: 0.9744 Epoch 5/6 48000/48000 [==============================] - 5s 101us/step - loss: 0.0843 - accuracy: 0.9767 Epoch 6/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.0760 - accuracy: 0.9802 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_37" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_73 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_161 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_74 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_162 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_37 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_73 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_37 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_89 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_163 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_90 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_164 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_74 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_91 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_165 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 110us/step - loss: 0.3692 - accuracy: 0.8888 Epoch 2/6 48000/48000 [==============================] - 5s 104us/step - loss: 0.1547 - accuracy: 0.9573 Epoch 3/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.1164 - accuracy: 0.9682 Epoch 4/6 48000/48000 [==============================] - 5s 106us/step - loss: 0.0960 - accuracy: 0.9739 Epoch 5/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.0855 - accuracy: 0.9771 Epoch 6/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.0799 - accuracy: 0.9787 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_38" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_75 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_166 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_76 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_167 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_38 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_75 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_38 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_92 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_168 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_93 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_169 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_76 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_94 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_170 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 109us/step - loss: 0.3541 - accuracy: 0.8931 Epoch 2/6 48000/48000 [==============================] - 5s 104us/step - loss: 0.1614 - accuracy: 0.9559 Epoch 3/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.1266 - accuracy: 0.9664 Epoch 4/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.0996 - accuracy: 0.9723 Epoch 5/6 48000/48000 [==============================] - 5s 106us/step - loss: 0.0907 - accuracy: 0.9759 Epoch 6/6 48000/48000 [==============================] - 5s 101us/step - loss: 0.0828 - accuracy: 0.9781 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_39" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_77 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_171 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_78 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_172 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_39 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_77 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_39 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_95 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_173 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_96 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_174 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_78 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_97 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_175 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 7s 138us/step - loss: 0.3629 - accuracy: 0.8934 Epoch 2/6 48000/48000 [==============================] - 6s 128us/step - loss: 0.1662 - accuracy: 0.9545 Epoch 3/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.1245 - accuracy: 0.9667 Epoch 4/6 48000/48000 [==============================] - 5s 99us/step - loss: 0.1035 - accuracy: 0.9722 Epoch 5/6 48000/48000 [==============================] - 5s 105us/step - loss: 0.0910 - accuracy: 0.9767 Epoch 6/6 48000/48000 [==============================] - 5s 100us/step - loss: 0.0820 - accuracy: 0.9787 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_40" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_79 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_176 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_80 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_177 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_40 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_79 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_40 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_98 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_178 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_99 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_179 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_80 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_100 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_180 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 48000/48000 [==============================] - 5s 110us/step - loss: 0.3803 - accuracy: 0.8851 Epoch 2/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.1589 - accuracy: 0.9570 Epoch 3/6 48000/48000 [==============================] - 6s 125us/step - loss: 0.1235 - accuracy: 0.9664 Epoch 4/6 48000/48000 [==============================] - 5s 102us/step - loss: 0.1064 - accuracy: 0.9710 Epoch 5/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.0934 - accuracy: 0.9753 Epoch 6/6 48000/48000 [==============================] - 5s 103us/step - loss: 0.0875 - accuracy: 0.9760 dense_layer_sizes [64, 64] filters 8 kernel_size 3 pool_size 2 Model: "sequential_41" ________________________________________________________________________________ Layer (type) Output Shape Param # ================================================================================ conv2d_81 (Conv2D) (None, 26, 26, 8) 80 ________________________________________________________________________________ activation_181 (Activation) (None, 26, 26, 8) 0 ________________________________________________________________________________ conv2d_82 (Conv2D) (None, 24, 24, 8) 584 ________________________________________________________________________________ activation_182 (Activation) (None, 24, 24, 8) 0 ________________________________________________________________________________ max_pooling2d_41 (MaxPooling2D) (None, 12, 12, 8) 0 ________________________________________________________________________________ dropout_81 (Dropout) (None, 12, 12, 8) 0 ________________________________________________________________________________ flatten_41 (Flatten) (None, 1152) 0 ________________________________________________________________________________ dense_101 (Dense) (None, 64) 73792 ________________________________________________________________________________ activation_183 (Activation) (None, 64) 0 ________________________________________________________________________________ dense_102 (Dense) (None, 64) 4160 ________________________________________________________________________________ activation_184 (Activation) (None, 64) 0 ________________________________________________________________________________ dropout_82 (Dropout) (None, 64) 0 ________________________________________________________________________________ dense_103 (Dense) (None, 10) 650 ________________________________________________________________________________ activation_185 (Activation) (None, 10) 0 ================================================================================ Total params: 79,266 Trainable params: 79,266 Non-trainable params: 0 ________________________________________________________________________________ Epoch 1/6 60000/60000 [==============================] - 8s 129us/step - loss: 0.3397 - accuracy: 0.8988 Epoch 2/6 60000/60000 [==============================] - 7s 124us/step - loss: 0.1434 - accuracy: 0.9614 Epoch 3/6 60000/60000 [==============================] - 6s 100us/step - loss: 0.1131 - accuracy: 0.9692 Epoch 4/6 60000/60000 [==============================] - 6s 107us/step - loss: 0.0947 - accuracy: 0.9740 Epoch 5/6 60000/60000 [==============================] - 6s 102us/step - loss: 0.0839 - accuracy: 0.9781 Epoch 6/6 60000/60000 [==============================] - 6s 102us/step - loss: 0.0767 - accuracy: 0.9796 The parameters of the best model are: {'dense_layer_sizes': [64, 64], 'epochs': 6, 'filters': 8, 'kernel_size': 3, 'pool_size': 2} 10000/10000 [==============================] - 1s 73us/step loss : 0.047322944842268046 accuracy : 0.9843999743461609