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silviacamplani/distilbert-finetuned-dapt-ner-ai
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.9448
- Validation Loss: 0.9212
- Train Precision: 0.3164
- Train Recall: 0.3186
- Train F1: 0.3175
- Train Accuracy: 0.7524
- 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': 1e-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 | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 2.6857 | 1.8199 | 0.0 | 0.0 | 0.0 | 0.6480 | 0 |
| 1.6775 | 1.4868 | 0.0 | 0.0 | 0.0 | 0.6480 | 1 |
| 1.3847 | 1.2452 | 0.0938 | 0.0102 | 0.0184 | 0.6565 | 2 |
| 1.2067 | 1.1198 | 0.1659 | 0.1244 | 0.1422 | 0.7077 | 3 |
| 1.0946 | 1.0321 | 0.2255 | 0.1925 | 0.2077 | 0.7225 | 4 |
| 1.0057 | 0.9640 | 0.2835 | 0.2777 | 0.2806 | 0.7433 | 5 |
| 0.9448 | 0.9212 | 0.3164 | 0.3186 | 0.3175 | 0.7524 | 6 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
