FBeta score in fastai: 'macro' vs 'weighted'

Hi,

I changed it in the following way, without the intended effect though. It still returns nan.

fbeta = FBeta(average='weighted')

learn = create_cnn(data, models.resnet50, metrics=[error_rate, fbeta],
                   callback_fns=ShowGraph)

This is what you mean with passing a function right?

By the way, passing macro instead of weighted does work. So maybe its due to this argument. I’m interested in the weighted error though!