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yemen2016/nbbert
nbbert is a token classification model from yemen2016. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-4.0.
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 NbAiLab/nb-bert-base on the None dataset. It achieves the following results on the evaluation set:
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss |
|---|---|---|---|---|---|---|---|
| No log | 0.9412 | 8 | 0.4361 | 0.6823 | 0.4361 | 0.3171 | 0.8924 |
| No log | 2.0 | 17 | 0.8851 | 0.8758 | 0.8851 | 0.8748 | 0.4652 |
| No log | 2.9412 | 25 | 0.8281 | 0.8333 | 0.8281 | 0.8204 | 0.5819 |
| No log | 4.0 | 34 | 0.8759 | 0.8922 | 0.8759 | 0.8749 | 0.4312 |
| No log | 4.9412 | 42 | 0.8550 | 0.8762 | 0.8550 | 0.8548 | 0.5312 |
| No log | 6.0 | 51 | 0.8944 | 0.8940 | 0.8944 | 0.8941 | 0.3318 |
| No log | 6.9412 | 59 | 0.9209 | 0.9255 | 0.9209 | 0.9210 | 0.3824 |
| No log | 8.0 | 68 | 0.9213 | 0.9282 | 0.9213 | 0.9219 | 0.4385 |
| No log | 8.9412 | 76 | 0.9205 | 0.9226 | 0.9205 | 0.9205 | 0.3830 |
| No log | 10.0 | 85 | 0.9249 | 0.9309 | 0.9249 | 0.9252 | 0.4137 |
| No log | 10.9412 | 93 | 0.9269 | 0.9310 | 0.9269 | 0.9270 | 0.4014 |
| No log | 12.0 | 102 | 0.9293 | 0.9321 | 0.9293 | 0.9293 | 0.3923 |
| No log | 12.9412 | 110 | 0.9277 | 0.9320 | 0.9277 | 0.9278 | 0.4565 |
| No log | 14.0 | 119 | 0.9305 | 0.9342 | 0.9305 | 0.9305 | 0.4166 |
| No log | 14.9412 | 127 | 0.9281 | 0.9325 | 0.9281 | 0.9282 | 0.4512 |
| No log | 16.0 | 136 | 0.9297 | 0.9336 | 0.9297 | 0.9298 | 0.4465 |
| No log | 16.9412 | 144 | 0.9273 | 0.9318 | 0.9273 | 0.9274 | 0.4624 |
| No log | 18.0 | 153 | 0.9277 | 0.9321 | 0.9277 | 0.9278 | 0.4593 |
| No log | 18.8235 | 160 | 0.9305 | 0.9342 | 0.9305 | 0.9305 | 0.4443 |