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ai-forever / ner-bert

BERT-NER (nert-bert) with google bert https://github.com/google-research.

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should we calculate F1-score with micro-average or macro-average?

Junpliu opened this issue · comments

commented

In the jupyter notebook "conll2003 BERTBiLSTMCRF" in the "examples" folder, the result report is as follow:

image

I notice you put macro-avg "0.9221" in the "README.md" file, but it seems like that the code at "https://paperswithcode.com/sota/named-entity-recognition-ner-on-conll-2003" adopt the micro-avg value as the final F1-value.

I would appreciate it very much if you can tell me why, thanks.