Feedforward Neural Network - Model Optimization #3

 

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

 

Searched combinations:

n_hidden_layers = 3 or 4

neurons_in_layer = 64 or 128

dropout = 0 or 0.5

activation_function = relu or selu

 

Fixed values:

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: 4608

searched time: 7h14m17s

 

BEST Result

 


Epoch 249/300:

loss: 0.5427 - accuracy: 0.9566

val_loss: 0.5808 - val_accuracy: 0.9405


Using 784 samples for training and 336 for validation

 

10 best results (optimization)





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