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README.md
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- F1: 0.9536
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# Model Performance
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This fine-tuned model is topped on the best scores (94.6%) from [Named Entity Recognition (NER) on CoNLL 2003 (English)]((https://paperswithcode.com/sota/named-entity-recognition-ner-on-conll-2003)).
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[the ConLL2003 Token Classification benchmark](https://paperswithcode.com/sota/token-classification-on-conll2003), This fine-tuned Model has achieved 95.36%.
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- F1: 0.9536
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# Model Performance
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- 1st Place: This fine-tuned model is topped on the best scores (94.6%) from [Named Entity Recognition (NER) on CoNLL 2003 (English)]((https://paperswithcode.com/sota/named-entity-recognition-ner-on-conll-2003)).
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- 6th Place: This fine-tuned model is ranked in the 6th place from the [Token Classification on conll2003 leaderboard](https://paperswithcode.com/sota/token-classification-on-conll2003)
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[the ConLL2003 Token Classification benchmark](https://paperswithcode.com/sota/token-classification-on-conll2003), This fine-tuned Model has achieved 95.36%.
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