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ajtamayoh/NLP-CIC-WFU_Clinical_Cases_NER_mBERT_cased_fine_tuned
NLP-CIC-WFU_Clinical_Cases_NER_mBERT_cased_fine_tuned is a token classification model from ajtamayoh. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
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 bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 94 | 0.0484 | 0.9002 | 0.6340 | 0.7440 | 0.9876 |
| No log | 2.0 | 188 | 0.0436 | 0.9095 | 0.6599 | 0.7649 | 0.9887 |
| No log | 3.0 | 282 | 0.0462 | 0.8545 | 0.7043 | 0.7722 | 0.9883 |
| No log | 4.0 | 376 | 0.0456 | 0.9058 | 0.6761 | 0.7743 | 0.9894 |
| No log | 5.0 | 470 | 0.0447 | 0.9194 | 0.6836 | 0.7841 | 0.9900 |
| 0.0426 | 6.0 | 564 | 0.0480 | 0.8917 | 0.7026 | 0.7859 | 0.9897 |
| 0.0426 | 7.0 | 658 | 0.0501 | 0.8961 | 0.7009 | 0.7865 | 0.9898 |