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bert-cased-ner-fcit499
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0404
- Precision: 0.9417
- Recall: 0.9502
- F1: 0.9460
- Accuracy: 0.9905
Model description
More information neededx
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 157 | 0.0578 | 0.8782 | 0.8976 | 0.8878 | 0.9825 |
| No log | 2.0 | 314 | 0.0425 | 0.9317 | 0.9343 | 0.9330 | 0.9885 |
| No log | 3.0 | 471 | 0.0391 | 0.9381 | 0.9433 | 0.9407 | 0.9897 |
| 0.1097 | 4.0 | 628 | 0.0397 | 0.9377 | 0.9467 | 0.9422 | 0.9900 |
| 0.1097 | 5.0 | 785 | 0.0404 | 0.9417 | 0.9502 | 0.9460 | 0.9905 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
