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MayaGalvez/bert-base-multilingual-cased-finetuned-pos
bert-base-multilingual-cased-finetuned-pos is a token classification model from MayaGalvez. 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 |
|---|---|---|---|---|---|---|---|
| 0.7663 | 0.27 | 200 | 0.2047 | 0.9318 | 0.9312 | 0.9315 | 0.9388 |
| 0.5539 | 0.53 | 400 | 0.1815 | 0.9381 | 0.9404 | 0.9392 | 0.9460 |
| 0.5222 | 0.8 | 600 | 0.1787 | 0.9400 | 0.9424 | 0.9412 | 0.9468 |
| 0.5084 | 1.07 | 800 | 0.1591 | 0.9470 | 0.9463 | 0.9467 | 0.9519 |
| 0.4703 | 1.33 | 1000 | 0.1622 | 0.9456 | 0.9458 | 0.9457 | 0.9510 |
| 0.5005 | 1.6 | 1200 | 0.1666 | 0.9470 | 0.9464 | 0.9467 | 0.9519 |
| 0.4677 | 1.87 | 1400 | 0.1583 | 0.9483 | 0.9483 | 0.9483 | 0.9532 |
| 0.4704 | 2.13 | 1600 | 0.1635 | 0.9472 | 0.9475 | 0.9473 | 0.9528 |
| 0.4639 | 2.4 | 1800 | 0.1569 | 0.9475 | 0.9488 | 0.9482 | 0.9536 |
| 0.4627 | 2.67 | 2000 | 0.1605 | 0.9474 | 0.9478 | 0.9476 | 0.9527 |
| 0.4608 | 2.93 | 2200 | 0.1535 | 0.9485 | 0.9495 | 0.9490 | 0.9538 |
| 0.4306 | 3.2 | 2400 | 0.1646 | 0.9489 | 0.9487 | 0.9488 | 0.9536 |
| 0.4583 | 3.47 | 2600 | 0.1642 | 0.9488 | 0.9495 | 0.9491 | 0.9539 |
| 0.453 | 3.73 | 2800 | 0.1646 | 0.9498 | 0.9505 | 0.9501 | 0.9554 |
| 0.4347 | 4.0 | 3000 | 0.1629 | 0.9494 | 0.9504 | 0.9499 | 0.9552 |
| 0.4425 | 4.27 | 3200 | 0.1738 | 0.9495 | 0.9502 | 0.9498 | 0.9550 |
| 0.4335 | 4.53 | 3400 | 0.1733 | 0.9499 | 0.9506 | 0.9503 | 0.9550 |
| 0.4306 | 4.8 | 3600 | 0.1736 | 0.9499 | 0.9504 | 0.9501 | 0.9551 |