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allasahithya/retrained_ner
retrained_ner is a token classification model from allasahithya. 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-uncased on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1292 | 1.0 | 878 | 0.0580 | 0.9201 | 0.9355 | 0.9277 | 0.9836 |
| 0.0394 | 2.0 | 1756 | 0.0613 | 0.9283 | 0.9415 | 0.9349 | 0.9847 |
| 0.0207 | 3.0 | 2634 | 0.0635 | 0.9398 | 0.9490 | 0.9444 | 0.9865 |
| 0.0117 | 4.0 | 3512 | 0.0688 | 0.9363 | 0.9455 | 0.9409 | 0.9857 |
| 0.0074 | 5.0 | 4390 | 0.0691 | 0.9416 | 0.9480 | 0.9448 | 0.9864 |
| 0.0043 | 6.0 | 5268 | 0.0803 | 0.9356 | 0.9466 | 0.9411 | 0.9861 |
| 0.0035 | 7.0 | 6146 | 0.0801 | 0.9435 | 0.9508 | 0.9471 | 0.9870 |
| 0.0021 | 8.0 | 7024 | 0.0825 | 0.9394 | 0.9491 | 0.9442 | 0.9860 |
| 0.0015 | 9.0 | 7902 | 0.0800 | 0.9421 | 0.9489 | 0.9455 | 0.9865 |
| 0.001 | 10.0 | 8780 | 0.0829 | 0.9435 | 0.9497 | 0.9466 | 0.9868 |