model_checkpoint = ModelCheckpoint(filepath='./multiflow_6_with_angle', save_best_only=True, monitor='val_loss') early_stop = EarlyStopping(monitor='val_loss', patience=10) plateu = ReduceLROnPlateau(monitor='val_loss', factor=0.1, patience=4) tb = TensorBoard(log_dir='./logs', histogram_freq=0, batch_size=32, write_graph=True, write_grads=True, write_images=True, embeddings_freq=0, embeddings_layer_names=None, embeddings_metadata=None) model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) model.fit([bands_train, inc_angles_train], icebergs_train, validation_data=([bands_test, inc_angles_test], icebergs_test), batch_size=32, epochs=80, callbacks=[model_checkpoint, early_stop, plateu, tb])