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afrodp95/distilbert-base-uncased-finetuned-job-skills-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: 0.0923
- Validation Loss: 0.1313
- Train Precision: 0.3601
- Train Recall: 0.4922
- Train F1: 0.4159
- Train Accuracy: 0.9522
- Epoch: 5
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': 3e-05, 'decay_steps': 1386, '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 |
|---|---|---|---|---|---|---|
| 0.3257 | 0.1935 | 0.3122 | 0.2144 | 0.2542 | 0.9521 | 0 |
| 0.1564 | 0.1464 | 0.3503 | 0.3423 | 0.3463 | 0.9546 | 1 |
| 0.1257 | 0.1365 | 0.3593 | 0.4893 | 0.4143 | 0.9522 | 2 |
| 0.1102 | 0.1318 | 0.3607 | 0.4692 | 0.4079 | 0.9521 | 3 |
| 0.1002 | 0.1305 | 0.3504 | 0.4941 | 0.4100 | 0.9515 | 4 |
| 0.0923 | 0.1313 | 0.3601 | 0.4922 | 0.4159 | 0.9522 | 5 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.6.1
- Tokenizers 0.13.2
