Hi! The new train recipe function returns a (best_scores, baseline) tuple – best_scores is an instance of spaCy's Scorer, which includes overall accuracy scores, as well as scores per label.
The train-curve mostly just runs train with different portions of the data and then outputs the best score for each training run at the end. So you could write your own version of the recipe that prints the best_scores.textcats_per_cat instead of using the default results printer. (You can find the recipe in recipes/train.py in your Prodigy installation – it should be pretty straightforward to copy, because it mostly just calls train() with arguments. To find the location of your Prodigy installation, you can run prodigy stats).