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silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data_3labels
This model is a fine-tuned version of silviacamplani/distilbert-base-uncased-finetuned-ai_data on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.6153
- Validation Loss: 0.5610
- Train Precision: 0.0
- Train Recall: 0.0
- Train F1: 0.0
- Train Accuracy: 0.8840
- 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': 1e-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 | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.6831 | 1.5093 | 0.0031 | 0.0020 | 0.0024 | 0.8573 | 0 |
| 1.3863 | 1.2247 | 0.0 | 0.0 | 0.0 | 0.8839 | 1 |
| 1.1078 | 0.9646 | 0.0 | 0.0 | 0.0 | 0.8840 | 2 |
| 0.8884 | 0.7566 | 0.0 | 0.0 | 0.0 | 0.8840 | 3 |
| 0.7235 | 0.6484 | 0.0 | 0.0 | 0.0 | 0.8840 | 4 |
| 0.6686 | 0.6034 | 0.0 | 0.0 | 0.0 | 0.8840 | 5 |
| 0.6541 | 0.5804 | 0.0 | 0.0 | 0.0 | 0.8840 | 6 |
| 0.6347 | 0.5687 | 0.0 | 0.0 | 0.0 | 0.8840 | 7 |
| 0.6147 | 0.5630 | 0.0 | 0.0 | 0.0 | 0.8840 | 8 |
| 0.6153 | 0.5610 | 0.0 | 0.0 | 0.0 | 0.8840 | 9 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
