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Ioana23/bert-finetuned-resumes-ner-2
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: 0.2007
- Validation Loss: 0.3219
- Epoch: 6
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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 350, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 0.9040 | 0.6209 | 0 |
| 0.4516 | 0.4323 | 1 |
| 0.3550 | 0.4498 | 2 |
| 0.2872 | 0.4073 | 3 |
| 0.2416 | 0.3226 | 4 |
| 0.2169 | 0.3442 | 5 |
| 0.2007 | 0.3219 | 6 |
Framework versions
- Transformers 4.32.1
- TensorFlow 2.10.0
- Datasets 2.14.4
- Tokenizers 0.13.3
