Your judge scores 91% accuracy on a held-out set. Do yo...

A strong answer requires looking beyond a raw accuracy percentage. If the held-out set is skewed, a high accuracy score can be misleading, as the model might be defaulting to the majority class label. To properly evaluate performance, one must ask for the class distribution and examine metrics like macro-F1 or per-class recall to understand if the model is actually learning the discriminating features of the data.