Cool, thanks.
Is there documentation on which hyperparameters can be tuned and what sensible ranges might be? The code contains the drop and size parameters, but there are probably also parameters for the layers etc of the neural net?
Edit: I found your answer here [Imbalanced classes in a multiclass textcat leads to completely biased predictions] which subclasses the textcat model to change the topology. Is that what I should be looking at? I guess I could also decide to add a softmax to enforce one-topic-per-document (assuming that’s what we want), but that probably means changing / copy-pasting the _ml.build_text_classier, right?