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ohss117/bert-finetuned-ner_v3
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0106
- Validation Loss: 0.0562
- Epoch: 4
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': 4390, '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 |
|---|---|---|
| 0.1762 | 0.0682 | 0 |
| 0.0449 | 0.0563 | 1 |
| 0.0263 | 0.0554 | 2 |
| 0.0160 | 0.0547 | 3 |
| 0.0106 | 0.0562 | 4 |
Framework versions
- Transformers 4.25.1
- TensorFlow 2.10.1
- Datasets 2.8.0
- Tokenizers 0.13.2
