model.add(Flatten()) model.add(Dense(256, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(10, activation='softmax')) #Train Model sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) model.compile(loss='categorical_crossentropy', optimizer=sgd) model.fit(x_train, y_train, batch_size=32, epochs=10) score = model.evaluate(x_test, y_test, batch_size=32)