resume_sorter
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: 1.6000
- Train Accuracy: 0.9309
- 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: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 225, '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}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Epoch |
|---|---|---|
| 3.0338 | 0.3025 | 0 |
| 2.5856 | 0.6257 | 1 |
| 2.1253 | 0.8646 | 2 |
| 1.7760 | 0.9144 | 3 |
| 1.6245 | 0.9309 | 4 |
| 1.5916 | 0.9309 | 5 |
| 1.6000 | 0.9309 | 6 |
Framework versions
- Transformers 4.25.1
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2