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silviacamplani/distilbert-uncase-direct-finetuning-ai-ner
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.6021
- Validation Loss: 1.6163
- Epoch: 9
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': 60, '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 |
|---|---|---|
| 3.2752 | 3.0320 | 0 |
| 2.7791 | 2.5293 | 1 |
| 2.2674 | 2.0340 | 2 |
| 1.8952 | 1.8222 | 3 |
| 1.7933 | 1.7669 | 4 |
| 1.7352 | 1.7158 | 5 |
| 1.6868 | 1.6706 | 6 |
| 1.6242 | 1.6412 | 7 |
| 1.5899 | 1.6234 | 8 |
| 1.6021 | 1.6163 | 9 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
