Validation scores

[nswinburne]

Thanks for the great RetinaNet examples. I'm training a model to recognize a single class (versus background) and validating on a held-out labeled dataset. I load in the new validation dataset and run:

learn.validate(data_test.valid_dl)

This returns [0.34860164, 0.774676853563362]

For a one-class approach, I'm assuming the first returned value is the Validation Loss and the 2nd is the class Average Precision. Is that correct?