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fashion_results.txt
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=======================================================================
Model name: fashion-1-16-256-0.001-7
The combination: 1,
learning rate: 0.001,
epochs: 16,
batch size: 256,
seed: 7
32, 64; 16, 32 in conv1 and conv2; 64 double Dense with dr 0.5
Training time: 1298.98 seconds
Training Accuracy: 89.08%
Test accuracy: 91.21%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 32) 160
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 64) 8256
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 64) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 14, 14, 16) 4112
_________________________________________________________________
conv2d_4 (Conv2D) (None, 14, 14, 32) 2080
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1568) 0
_________________________________________________________________
dense_1 (Dense) (None, 64) 100416
_________________________________________________________________
dropout_1 (Dropout) (None, 64) 0
_________________________________________________________________
dense_2 (Dense) (None, 64) 4160
_________________________________________________________________
dropout_2 (Dropout) (None, 64) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 650
=================================================================
Total params: 119,834
Trainable params: 119,834
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-1-24-128-0.001-7
The combination: 1,
learning rate: 0.001,
epochs: 24,
batch size: 128,
seed: 7
64; 64, 64 in conv1 and conv2; 256 double Dense with dr 0.4
Training time: 1985.55 seconds
Training Accuracy: 97.69%
Test accuracy: 92.34%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 64) 320
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 14, 14, 64) 16448
_________________________________________________________________
conv2d_3 (Conv2D) (None, 14, 14, 64) 16448
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 64) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 3136) 0
_________________________________________________________________
dense_1 (Dense) (None, 256) 803072
_________________________________________________________________
dropout_1 (Dropout) (None, 256) 0
_________________________________________________________________
dense_2 (Dense) (None, 256) 65792
_________________________________________________________________
dropout_2 (Dropout) (None, 256) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 2570
=================================================================
Total params: 904,650
Trainable params: 904,650
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-1-24-128-0.001-7-m3
The combination: 1,
learning rate: 0.001,
epochs: 24,
batch size: 128,
seed: 7
64, 64; 32, 32 in conv1 and conv2; 128 double Dense with dr 0.4
Training time: 3338.06 seconds
Training Accuracy: 95.86%
Test accuracy: 92.62%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 64) 320
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 64) 16448
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 64) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 14, 14, 32) 8224
_________________________________________________________________
conv2d_4 (Conv2D) (None, 14, 14, 32) 4128
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1568) 0
_________________________________________________________________
dense_1 (Dense) (None, 128) 200832
_________________________________________________________________
dropout_1 (Dropout) (None, 128) 0
_________________________________________________________________
dense_2 (Dense) (None, 128) 16512
_________________________________________________________________
dropout_2 (Dropout) (None, 128) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 1290
=================================================================
Total params: 247,754
Trainable params: 247,754
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-1-16-128-0.001-7-m4
The combination: 1,
learning rate: 0.001,
epochs: 16,
batch size: 128,
seed: 7
32, 32; 32, 32 in conv1 and conv2; 100 double Dense with dr 0.4
Training time: 1026.29 seconds
Training Accuracy: 93.81%
Test accuracy: 92.64%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 32) 160
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 32) 4128
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 32) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 14, 14, 32) 4128
_________________________________________________________________
conv2d_4 (Conv2D) (None, 14, 14, 32) 4128
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1568) 0
_________________________________________________________________
dense_1 (Dense) (None, 100) 156900
_________________________________________________________________
dropout_1 (Dropout) (None, 100) 0
_________________________________________________________________
dense_2 (Dense) (None, 100) 10100
_________________________________________________________________
dropout_2 (Dropout) (None, 100) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 1010
=================================================================
Total params: 180,554
Trainable params: 180,554
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-1-15-256-0.001-7-m5
The combination: 1,
learning rate: 0.001,
epochs: 15,
batch size: 256,
seed: 7
32, 64; 32 in conv1 and conv2; 100 double Dense with dr 0.4
Training time: 1278.96 seconds
Training Accuracy: 93.17%
Test accuracy: 92.10%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 32) 160
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 64) 8256
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 64) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 14, 14, 32) 8224
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1568) 0
_________________________________________________________________
dense_1 (Dense) (None, 100) 156900
_________________________________________________________________
dropout_1 (Dropout) (None, 100) 0
_________________________________________________________________
dense_2 (Dense) (None, 100) 10100
_________________________________________________________________
dropout_2 (Dropout) (None, 100) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 1010
=================================================================
Total params: 184,650
Trainable params: 184,650
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-1-18-128-0.001-7-m6
The combination: 1,
learning rate: 0.001,
epochs: 18,
batch size: 128,
seed: 7
32; 32 in conv1 and conv2; 100 double Dense with dr 0.4
Training time: 484.17 seconds
Training Accuracy: 96.31%
Test accuracy: 91.67%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 32) 160
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 32) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 14, 14, 32) 4128
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 7, 7, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1568) 0
_________________________________________________________________
dense_1 (Dense) (None, 100) 156900
_________________________________________________________________
dense_2 (Dense) (None, 100) 10100
_________________________________________________________________
dense_3 (Dense) (None, 10) 1010
=================================================================
Total params: 172,298
Trainable params: 172,298
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-2-15-64-0.001-7-m7
The combination: 2,
learning rate: 0.001,
epochs: 15,
batch size: 64,
seed: 7
32 32 in conv with constant bias; 128 single Dense
Training time: 826.59 seconds
Training Accuracy: 98.81%
Test accuracy: 90.95%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
batch_normalization_1 (Batch (None, 28, 28, 1) 4
_________________________________________________________________
conv2d_1 (Conv2D) (None, 28, 28, 32) 160
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 32) 4128
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 32) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 6272) 0
_________________________________________________________________
dense_1 (Dense) (None, 128) 802944
_________________________________________________________________
dense_2 (Dense) (None, 10) 1290
=================================================================
Total params: 808,526
Trainable params: 808,524
Non-trainable params: 2
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-2-10-256-0.001-7-m8
The combination: 2,
learning rate: 0.001,
epochs: 10,
batch size: 256,
seed: 7
single 64 in conv with Average Pooling; 64 double Dense
Training time: 360.66 seconds
Training Accuracy: 92.17%
Test accuracy: 90.05%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 28, 28, 64) 320
_________________________________________________________________
average_pooling2d_1 (Average (None, 14, 14, 64) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 12544) 0
_________________________________________________________________
dense_1 (Dense) (None, 64) 802880
_________________________________________________________________
dense_2 (Dense) (None, 64) 4160
_________________________________________________________________
dense_3 (Dense) (None, 10) 650
=================================================================
Total params: 808,010
Trainable params: 808,010
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-3-16-64-0.001-7-m9
The combination: 3,
learning rate: 0.001,
epochs: 16,
batch size: 64,
seed: 7
256 double Dense with 0.5 drop out rate
Training time: 109.99 seconds
Training Accuracy: 87.37%
Test accuracy: 87.45%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
flatten_1 (Flatten) (None, 784) 0
_________________________________________________________________
dense_1 (Dense) (None, 256) 200960
_________________________________________________________________
dropout_1 (Dropout) (None, 256) 0
_________________________________________________________________
dense_2 (Dense) (None, 256) 65792
_________________________________________________________________
dropout_2 (Dropout) (None, 256) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 2570
=================================================================
Total params: 269,322
Trainable params: 269,322
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-3-30-32-0.001-7-m10
The combination: 3,
learning rate: 0.001,
epochs: 30,
batch size: 32,
seed: 7
256 double Dense with 0.6 drop out rate
Training time: 289.24 seconds
Training Accuracy: 85.82%
Test accuracy: 86.77%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
flatten_1 (Flatten) (None, 784) 0
_________________________________________________________________
dense_1 (Dense) (None, 256) 200960
_________________________________________________________________
dropout_1 (Dropout) (None, 256) 0
_________________________________________________________________
dense_2 (Dense) (None, 256) 65792
_________________________________________________________________
dropout_2 (Dropout) (None, 256) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 2570
=================================================================
Total params: 269,322
Trainable params: 269,322
Non-trainable params: 0
_________________________________________________________________
=======================================================================
=======================================================================
Model name: fashion-3-30-32-0.001-7-m11
The combination: 3,
learning rate: 0.001,
epochs: 30,
batch size: 32,
seed: 7
256 double Dense with 0.5 drop out rate
Training time: 296.45 seconds
Training Accuracy: 87.70%
Test accuracy: 88.30%
The Architecture of the Model:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
flatten_1 (Flatten) (None, 784) 0
_________________________________________________________________
dense_1 (Dense) (None, 256) 200960
_________________________________________________________________
dropout_1 (Dropout) (None, 256) 0
_________________________________________________________________
dense_2 (Dense) (None, 256) 65792
_________________________________________________________________
dropout_2 (Dropout) (None, 256) 0
_________________________________________________________________
dense_3 (Dense) (None, 10) 2570
=================================================================
Total params: 269,322
Trainable params: 269,322
Non-trainable params: 0
_________________________________________________________________
=======================================================================