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chintagunta85/electramed-small-BC5CDR-ner
electramed-small-BC5CDR-ner is a token classification model from chintagunta85. 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 giacomomiolo/electramed_small_scivocab on the bc5_cdr 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 |
|---|---|---|---|---|---|---|---|
| 0.7177 | 1.0 | 286 | 0.6902 | 0.0 | 0.0 | 0.0 | 0.8864 |
| 0.1561 | 2.0 | 572 | 0.3210 | 0.7334 | 0.8104 | 0.7700 | 0.9636 |
| 0.2511 | 3.0 | 858 | 0.2064 | 0.7809 | 0.8711 | 0.8236 | 0.9666 |
| 0.0512 | 4.0 | 1144 | 0.1599 | 0.7937 | 0.8751 | 0.8324 | 0.9689 |
| 0.083 | 5.0 | 1430 | 0.1449 | 0.7983 | 0.8804 | 0.8373 | 0.9679 |
| 0.0412 | 6.0 | 1716 | 0.1315 | 0.8141 | 0.8825 | 0.8469 | 0.9701 |
| 0.1437 | 7.0 | 2002 | 0.1258 | 0.8227 | 0.8758 | 0.8485 | 0.9699 |
| 0.1894 | 8.0 | 2288 | 0.1226 | 0.8141 | 0.8833 | 0.8473 | 0.9696 |
| 0.0236 | 9.0 | 2574 | 0.1220 | 0.8160 | 0.8824 | 0.8479 | 0.9694 |
| 0.0602 | 10.0 | 2860 | 0.1227 | 0.8092 | 0.8829 | 0.8444 | 0.9686 |