Hi everyone,
I fine tuned a BERT model to perform a NER task using a BILUO scheme and I have to calculate F1 score.
However, in named-entity recognition, f1 score is calculated per entity, not token.
Moreover, there is the Word-Piece “problem” and the BILUO format, so I should:
- aggregate the subwords in words
- remove the prefixes “B-”, “I-”, “L-” from each entity
- calculate the F1 score on the entity
Before I spend hours (if not days) to try to implement such code, I would like to know if an implemented solution already exists.
Thanks in advance