flatten = keras.layers.Flatten()(pool1)
dense1 = keras.layers.Dense(1200, activation='relu')(flatten)
output = keras.layers.Dense(1, activation = tf.nn.relu,name="output")(dense1)
model = tf.keras.Model(inputs=input_layer, outputs=output)

model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.000002),
                                              loss="mean_squared_error",
                                              metrics=["acc"])

metrics = model.fit(dataset_array_trainning, label_array_trainning,
                    batch_size=10,
                    epochs=15,
                    validation_data=(dataset_array_testing, label_array_testing))