cls_answerable_loss and match_loss

[huydang2106]

I have questions about some details in training.
in your paper, you said your backbone model for NER experiment is proposed in "A Unified MRC Framework for Named Entity Recognition". But when I look in the code and run the experiment to reproduce the reported results, I found that you ignore the match_loss (match_loss is introduced to teach the model to match which predicted start token with which predicted end token).
So how we can inference this model in the case of sentence with multiple Ner entities?
Also, you introduce a new loss - cls_answerable_loss to teach model to classify whether input contains entity or loss. Why do you not mention this loss in your paper.
Thank you.