notmaineyy/distilbert-base-uncased-finetuned-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: 0.0344
- Validation Loss: 0.0633
- Train Precision: 0.9181
- Train Recall: 0.9322
- Train F1: 0.9251
- Train Accuracy: 0.9823
- 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: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, '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}
- training_precision: float32
Training results
| Train Loss |
Validation Loss |
Train Precision |
Train Recall |
Train F1 |
Train Accuracy |
Epoch |
| 0.2048 |
0.0749 |
0.8898 |
0.9129 |
0.9012 |
0.9784 |
0 |
| 0.0556 |
0.0621 |
0.9150 |
0.9300 |
0.9224 |
0.9819 |
1 |
| 0.0344 |
0.0633 |
0.9181 |
0.9322 |
0.9251 |
0.9823 |
2 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
