Minor learner loading bug with vs without custom loss function

So I found a weird bug maybe it’s because I use a custom dataset/loss function but still though I should let you guys know.
When I load my model I get different results with and without a loss function. Also the results without are very weird, they do not seems to make sense.

Here a link to the notebook:

Learner always has a loss function, it defaults to F.cross_entropy when you’re not using fastai to build your DataBunch, so that’s why you have those different results.
So the first section isn’t really without loss function, but with crossentropy :wink:

Oke but still it is weird that the predictions are different when the loss function changes. Note I do not train the model (with these different loss functions) here I only load and predict here.