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Aleksandar/bert-srb-ner-setimes
bert-srb-ner-setimes is a token classification model from Aleksandar. 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 was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 104 | 0.2281 | 0.6589 | 0.7001 | 0.6789 | 0.9350 |
| No log | 2.0 | 208 | 0.1833 | 0.7105 | 0.7694 | 0.7388 | 0.9470 |
| No log | 3.0 | 312 | 0.1573 | 0.7461 | 0.7778 | 0.7616 | 0.9525 |
| No log | 4.0 | 416 | 0.1489 | 0.7665 | 0.8091 | 0.7872 | 0.9557 |
| 0.1898 | 5.0 | 520 | 0.1445 | 0.7881 | 0.8327 | 0.8098 | 0.9587 |
| 0.1898 | 6.0 | 624 | 0.1473 | 0.7913 | 0.8316 | 0.8109 | 0.9601 |
| 0.1898 | 7.0 | 728 | 0.1558 | 0.8101 | 0.8347 | 0.8222 | 0.9620 |
| 0.1898 | 8.0 | 832 | 0.1616 | 0.8026 | 0.8302 | 0.8162 | 0.9612 |
| 0.1898 | 9.0 | 936 | 0.1716 | 0.8127 | 0.8409 | 0.8266 | 0.9631 |
| 0.0393 | 10.0 | 1040 | 0.1751 | 0.8140 | 0.8369 | 0.8253 | 0.9628 |
| 0.0393 | 11.0 | 1144 | 0.1775 | 0.8096 | 0.8420 | 0.8255 | 0.9626 |
| 0.0393 | 12.0 | 1248 | 0.1763 | 0.8161 | 0.8386 | 0.8272 | 0.9636 |
| 0.0393 | 13.0 | 1352 | 0.1949 | 0.8259 | 0.8400 | 0.8329 | 0.9634 |
| 0.0393 | 14.0 | 1456 | 0.1842 | 0.8205 | 0.8420 | 0.8311 | 0.9642 |
| 0.0111 | 15.0 | 1560 | 0.1862 | 0.8160 | 0.8493 | 0.8323 | 0.9646 |
| 0.0111 | 16.0 | 1664 | 0.1989 | 0.8176 | 0.8367 | 0.8270 | 0.9627 |
| 0.0111 | 17.0 | 1768 | 0.1945 | 0.8246 | 0.8409 | 0.8327 | 0.9638 |
| 0.0111 | 18.0 | 1872 | 0.1997 | 0.8270 | 0.8426 | 0.8347 | 0.9634 |
| 0.0111 | 19.0 | 1976 | 0.1917 | 0.8258 | 0.8491 | 0.8373 | 0.9651 |
| 0.0051 | 20.0 | 2080 | 0.1955 | 0.8229 | 0.8465 | 0.8345 | 0.9645 |