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Criser2013/NER-finetuning-XLM-RoBERTa-BIOBERT
NER-finetuning-XLM-RoBERTa-BIOBERT is a token classification model from Criser2013. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of raulgdp/xml-roberta-large-finetuned-ner on the biobert_json dataset. It achieves the following results on the evaluation set:
More information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1306 | 1.0 | 1224 | 0.1013 | 0.9299 | 0.9609 | 0.9451 | 0.9735 |
| 0.0996 | 2.0 | 2448 | 0.0932 | 0.9383 | 0.9656 | 0.9517 | 0.9777 |
| 0.0608 | 3.0 | 3672 | 0.0865 | 0.9493 | 0.9720 | 0.9605 | 0.9813 |
| 0.0445 | 4.0 | 4896 | 0.0927 | 0.9531 | 0.9729 | 0.9629 | 0.9819 |
| 0.0327 | 5.0 | 6120 | 0.0946 | 0.9498 | 0.9714 | 0.9605 | 0.9814 |