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favs_token_classification_v2
This model is a fine-tuned version of bert-base-cased on the token_classification_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5498
- Precision: 0.6610
- Recall: 0.8417
- F1: 0.7405
- Accuracy: 0.8575
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 2.2225 | 1.0 | 13 | 1.9093 | 0.3735 | 0.2230 | 0.2793 | 0.3808 |
| 1.9616 | 2.0 | 26 | 1.6124 | 0.3101 | 0.3525 | 0.3300 | 0.4877 |
| 1.7778 | 3.0 | 39 | 1.3562 | 0.3632 | 0.4964 | 0.4195 | 0.6219 |
| 1.4003 | 4.0 | 52 | 1.1595 | 0.4278 | 0.5755 | 0.4908 | 0.6685 |
| 1.2374 | 5.0 | 65 | 1.0260 | 0.4462 | 0.6259 | 0.5210 | 0.6904 |
| 1.1184 | 6.0 | 78 | 0.9223 | 0.4895 | 0.6691 | 0.5653 | 0.7205 |
| 0.8801 | 7.0 | 91 | 0.8179 | 0.5027 | 0.6763 | 0.5767 | 0.7397 |
| 0.8246 | 8.0 | 104 | 0.7591 | 0.5543 | 0.7338 | 0.6316 | 0.7699 |
| 0.7177 | 9.0 | 117 | 0.7037 | 0.5683 | 0.7482 | 0.6460 | 0.7890 |
| 0.6277 | 10.0 | 130 | 0.6652 | 0.5870 | 0.7770 | 0.6687 | 0.8 |
| 0.5744 | 11.0 | 143 | 0.6344 | 0.6011 | 0.7914 | 0.6832 | 0.8164 |
| 0.528 | 12.0 | 156 | 0.6117 | 0.6292 | 0.8058 | 0.7066 | 0.8329 |
| 0.4981 | 13.0 | 169 | 0.5919 | 0.6348 | 0.8129 | 0.7129 | 0.8384 |
| 0.4423 | 14.0 | 182 | 0.5841 | 0.6461 | 0.8273 | 0.7256 | 0.8438 |
| 0.4864 | 15.0 | 195 | 0.5781 | 0.6461 | 0.8273 | 0.7256 | 0.8521 |
| 0.3975 | 16.0 | 208 | 0.5677 | 0.6517 | 0.8345 | 0.7319 | 0.8548 |
| 0.3846 | 17.0 | 221 | 0.5563 | 0.6517 | 0.8345 | 0.7319 | 0.8548 |
| 0.3729 | 18.0 | 234 | 0.5503 | 0.6610 | 0.8417 | 0.7405 | 0.8575 |
| 0.3367 | 19.0 | 247 | 0.5504 | 0.6610 | 0.8417 | 0.7405 | 0.8575 |
| 0.3492 | 20.0 | 260 | 0.5498 | 0.6610 | 0.8417 | 0.7405 | 0.8575 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
