We see that in all cases the label-agnostic model outperforms standard fine- tuned BERT, often significantly.
we note that when going from universal POS tags to standard POS tags, the fine-tuned label-agnostic model manages to outperform the standard mostfrequent-tag-per-word baseline, which itself obtains slightly less than 92% accuracy.