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extended_distilBERT-finetuned-resumes-sections
This model is a fine-tuned version of Geotrend/distilbert-base-en-fr-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0321
- F1: 0.9735
- Roc Auc: 0.9850
- Accuracy: 0.9715
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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0283 | 1.0 | 2213 | 0.0247 | 0.9610 | 0.9763 | 0.9539 |
| 0.0153 | 2.0 | 4426 | 0.0223 | 0.9634 | 0.9789 | 0.9593 |
| 0.01 | 3.0 | 6639 | 0.0199 | 0.9702 | 0.9835 | 0.9675 |
| 0.0073 | 4.0 | 8852 | 0.0218 | 0.9710 | 0.9838 | 0.9690 |
| 0.0063 | 5.0 | 11065 | 0.0244 | 0.9706 | 0.9835 | 0.9684 |
| 0.0037 | 6.0 | 13278 | 0.0251 | 0.9700 | 0.9833 | 0.9684 |
| 0.004 | 7.0 | 15491 | 0.0273 | 0.9712 | 0.9837 | 0.9693 |
| 0.003 | 8.0 | 17704 | 0.0266 | 0.9719 | 0.9841 | 0.9695 |
| 0.0027 | 9.0 | 19917 | 0.0294 | 0.9697 | 0.9831 | 0.9679 |
| 0.0014 | 10.0 | 22130 | 0.0275 | 0.9714 | 0.9844 | 0.9690 |
| 0.0016 | 11.0 | 24343 | 0.0299 | 0.9714 | 0.9839 | 0.9697 |
| 0.0013 | 12.0 | 26556 | 0.0297 | 0.9719 | 0.9852 | 0.9697 |
| 0.0006 | 13.0 | 28769 | 0.0312 | 0.9711 | 0.9843 | 0.9697 |
| 0.0004 | 14.0 | 30982 | 0.0305 | 0.9731 | 0.9849 | 0.9720 |
| 0.0004 | 15.0 | 33195 | 0.0312 | 0.9723 | 0.9845 | 0.9704 |
| 0.0005 | 16.0 | 35408 | 0.0331 | 0.9716 | 0.9843 | 0.9697 |
| 0.0006 | 17.0 | 37621 | 0.0321 | 0.9735 | 0.9850 | 0.9715 |
| 0.0004 | 18.0 | 39834 | 0.0322 | 0.9731 | 0.9850 | 0.9711 |
| 0.0003 | 19.0 | 42047 | 0.0332 | 0.9722 | 0.9847 | 0.9706 |
| 0.0004 | 20.0 | 44260 | 0.0334 | 0.9720 | 0.9846 | 0.9704 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
