Feedforward Neural Network - Model Optimization #4

Using keras (python deep learning library), I am trying to find the best neural network model structure.

 

Searched combinations:

neurons_in_layer = 16 or 32 or 64 or 128

dropout = 0 or 0.2 or 0.5

activation_function = relu or selu

 

Fixed values:

n_hidden_layers = 3

model_optimizer = Adam

learning_rate = 0.001

max_epochs = 300

batch_size = 96

model_loss = sparse_categorical_crossentropy 

kernel_regularizer_per_layer = L1

early_stopping = val_loss ; patience = 20


model configurations: 1536

searched time: 2h34m41s

 

BEST Result

 

 

Epoch 300/300:

loss: 0.4666 - accuracy: 0.9745

val_loss: 0.5030 - val_accuracy: 0.9524

 


Using 784 samples for training and 336 for validation

 

10 best results (optimization)

 





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