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Ioana23/bert-finetuned-resumes-ner
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: 0.1439
- Validation Loss: 0.3965
- Epoch: 8
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': 500, '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 |
|---|---|---|
| 0.8008 | 0.5863 | 0 |
| 0.4590 | 0.4465 | 1 |
| 0.3443 | 0.3876 | 2 |
| 0.2827 | 0.3977 | 3 |
| 0.2285 | 0.3824 | 4 |
| 0.1962 | 0.3965 | 5 |
| 0.1699 | 0.3259 | 6 |
| 0.1559 | 0.4927 | 7 |
| 0.1439 | 0.3965 | 8 |
Framework versions
- Transformers 4.32.1
- TensorFlow 2.10.0
- Datasets 2.14.4
- Tokenizers 0.13.3
