Feedforward Neural Network - Model Optimization #1

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

 

Searched combinations:

n_hidden_layers = 2 or 3

neurons_in_layer = 32 or 64

dropout = 0 or 0.2

activation_function = relu or sigmoid or selu

model_optimizer = Adam or SGD or RMSprop

 

Fixed values:

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: 5616

searched time: 9h16m36s

 

BEST Result

 

Epoch 300/300:

loss: 0.4321 - accuracy: 0.9745

val_loss: 0.4490 - val_accuracy: 0.9583


Using 784 samples for training and 336 for validation

 

10 best results (optimization)

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