thanat/bert-finetuned-ner
This model is a fine-tuned version of bert-base-cased on the CoNLL-2003 dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0280
- Validation Loss: 0.0513
- Epoch: 2
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2634, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 0.1691 | 0.0630 | 0 |
| 0.0484 | 0.0529 | 1 |
| 0.0280 | 0.0513 | 2 |
Framework versions
- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2