Feedforward Neural Network - Model Optimization #2

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

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: 4096

searched time: 6h52m26s

 

BEST Result



 

Epoch 300/300:

loss: 0.4050 - accuracy: 0.9834

val_loss: 0.4435 - val_accuracy: 0.9554


Using 784 samples for training and 336 for validation

 

10 best results (optimization)


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