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yanekyuk/bert-cased-keyword-discriminator
bert-cased-keyword-discriminator is a token classification model from yanekyuk. 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-cased on an unknown 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 | Accuracy | F1 | Ent/precision | Ent/accuracy | Ent/f1 | Con/precision | Con/accuracy | Con/f1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1744 | 1.0 | 1875 | 0.1261 | 0.7176 | 0.7710 | 0.9494 | 0.7433 | 0.7586 | 0.8503 | 0.8018 | 0.6514 | 0.6561 | 0.6537 |
| 0.1261 | 2.0 | 3750 | 0.1041 | 0.7742 | 0.8057 | 0.9600 | 0.7896 | 0.8083 | 0.8816 | 0.8433 | 0.7185 | 0.6957 | 0.7070 |
| 0.0878 | 3.0 | 5625 | 0.0979 | 0.8176 | 0.8140 | 0.9655 | 0.8158 | 0.8518 | 0.8789 | 0.8651 | 0.7634 | 0.7199 | 0.7410 |
| 0.0625 | 4.0 | 7500 | 0.0976 | 0.8228 | 0.8643 | 0.9696 | 0.8430 | 0.8515 | 0.9182 | 0.8836 | 0.7784 | 0.7862 | 0.7823 |
| 0.0456 | 5.0 | 9375 | 0.1047 | 0.8304 | 0.8758 | 0.9704 | 0.8525 | 0.8758 | 0.9189 | 0.8968 | 0.7655 | 0.8133 | 0.7887 |
| 0.0342 | 6.0 | 11250 | 0.1207 | 0.8363 | 0.8887 | 0.9719 | 0.8617 | 0.8719 | 0.9274 | 0.8988 | 0.7846 | 0.8327 | 0.8080 |
| 0.0256 | 7.0 | 13125 | 0.1241 | 0.848 | 0.8892 | 0.9731 | 0.8681 | 0.8791 | 0.9299 | 0.9038 | 0.8019 | 0.8302 | 0.8158 |
| 0.0205 | 8.0 | 15000 | 0.1310 | 0.8522 | 0.8868 | 0.9732 | 0.8692 | 0.8874 | 0.9246 | 0.9056 | 0.8011 | 0.8320 | 0.8163 |