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silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data
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: 2.3549
- Validation Loss: 2.3081
- Train Precision: 0.0
- Train Recall: 0.0
- Train F1: 0.0
- Train Accuracy: 0.6392
- Epoch: 2
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': 18, '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 |
|---|---|---|---|---|---|---|
| 3.0905 | 2.8512 | 0.0 | 0.0 | 0.0 | 0.6376 | 0 |
| 2.6612 | 2.4783 | 0.0 | 0.0 | 0.0 | 0.6392 | 1 |
| 2.3549 | 2.3081 | 0.0 | 0.0 | 0.0 | 0.6392 | 2 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
