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conll2003-roberta-large
This model is a fine-tuned version of roberta-large on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0311
- Precision: 0.9657
- Recall: 0.9711
- F1: 0.9684
- Accuracy: 0.9942
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: 2e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1158 | 1.0 | 878 | 0.0448 | 0.9466 | 0.9541 | 0.9503 | 0.9915 |
| 0.03 | 2.0 | 1756 | 0.0326 | 0.9531 | 0.9645 | 0.9588 | 0.9930 |
| 0.0176 | 3.0 | 2634 | 0.0311 | 0.9587 | 0.9679 | 0.9632 | 0.9936 |
| 0.0088 | 4.0 | 3512 | 0.0311 | 0.9657 | 0.9711 | 0.9684 | 0.9942 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
