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evangeliazve/mpnet-base-articles-ner
mpnet-base-articles-ner is a token classification model from evangeliazve. 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 microsoft/mpnet-base on an unknown 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 | F1 |
|---|---|---|---|---|
| 1.8042 | 1.0 | 5 | 1.6278 | 0.0 |
| 1.5353 | 2.0 | 10 | 1.5332 | 0.0 |
| 1.499 | 3.0 | 15 | 1.4356 | 0.1781 |
| 1.343 | 4.0 | 20 | 1.3254 | 0.3789 |
| 1.2306 | 5.0 | 25 | 1.2572 | 0.5075 |
| 1.1427 | 6.0 | 30 | 1.1572 | 0.5700 |
| 1.0715 | 7.0 | 35 | 1.0875 | 0.6305 |
| 0.9679 | 8.0 | 40 | 1.0261 | 0.6667 |
| 0.9169 | 9.0 | 45 | 0.9924 | 0.6512 |
| 0.8447 | 10.0 | 50 | 0.9457 | 0.7137 |
| 0.8253 | 11.0 | 55 | 0.9216 | 0.7094 |
| 0.7493 | 12.0 | 60 | 0.9068 | 0.7303 |
| 0.7378 | 13.0 | 65 | 0.8896 | 0.7404 |
| 0.7039 | 14.0 | 70 | 0.8827 | 0.7398 |
| 0.7277 | 15.0 | 75 | 0.8632 | 0.7635 |
| 0.6758 | 16.0 | 80 | 0.8517 | 0.775 |
| 0.6642 | 17.0 | 85 | 0.8618 | 0.7449 |
| 0.6327 | 18.0 | 90 | 0.8522 | 0.7490 |
| 0.6238 | 19.0 | 95 | 0.8477 | 0.7500 |
| 0.6101 | 20.0 | 100 | 0.8471 | 0.7500 |