Created
April 18, 2021 18:26
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model = models.Sequential([ | |
layers.Dense(256, activation = 'relu', input_shape = Xtrain[0].shape), | |
layers.Dense(64, activation = 'relu'), | |
layers.Dense(16, activation = 'relu'), | |
layers.Dense(4, activation = 'softmax') | |
]) | |
cb = [callbacks.EarlyStopping(patience = 5, restore_best_weights = True)] | |
model.compile(optimizer=optimizers.Adam(0.0001), loss=losses.CategoricalCrossentropy(), metrics=['accuracy']) | |
history = model.fit(Xtrain, ytrain, epochs = 256, validation_data = (Xval, yval), callbacks = cb) |
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