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bert-base-cased
This model was trained from scratch on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3045
- Precision: 0.9245
- Recall: 0.9319
- F1: 0.9282
- Accuracy: 0.9333
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2707 | 1.0 | 1756 | 0.3120 | 0.9171 | 0.9263 | 0.9217 | 0.9267 |
0.1829 | 2.0 | 3512 | 0.2928 | 0.9189 | 0.9295 | 0.9242 | 0.9299 |
0.1411 | 3.0 | 5268 | 0.3045 | 0.9245 | 0.9319 | 0.9282 | 0.9333 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3