# Returned loss value is different than the loss printed with verbose

Could someone explain why the loss returned is different than the loss printed during the evaluation?

They are the same in the Tensorflow documentation https://www.tensorflow.org/guide/keras/train_and_evaluate

Code:

results = model.evaluate(test_data, test_target, verbose=2)
print("test loss, test acc:", results)


Output:

45/1 - 0s - loss: 1.2592 - mae: 0.7602
test loss, test acc: [1.05335361427731, 0.76020277]


The model.evaluate function predicts the output for the given input and then computes the metrics function specified in the model.compile.Based on y_true and y_pred and returns the computed metric value as the output.
You can use model.metrics_names property of your model to find out what each of those values corresponds to.