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fg-bert-sustainability-15-2.4e-05-0.02-64
This model is a fine-tuned version of Raccourci/fairguest-bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0686
- F1: 0.9127
- Roc Auc: 0.9540
- Accuracy: 0.8711
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: 2.4e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 55 | 0.2801 | 0.2031 | 0.5564 | 0.1830 |
| No log | 2.0 | 110 | 0.1533 | 0.8796 | 0.9282 | 0.8160 |
| No log | 3.0 | 165 | 0.0979 | 0.9116 | 0.9482 | 0.8669 |
| No log | 4.0 | 220 | 0.0844 | 0.9126 | 0.9507 | 0.8711 |
| No log | 5.0 | 275 | 0.0776 | 0.9110 | 0.9500 | 0.8701 |
| No log | 6.0 | 330 | 0.0732 | 0.9131 | 0.9507 | 0.8721 |
| No log | 7.0 | 385 | 0.0740 | 0.9116 | 0.9557 | 0.8669 |
| No log | 8.0 | 440 | 0.0711 | 0.9120 | 0.9553 | 0.8690 |
| No log | 9.0 | 495 | 0.0687 | 0.9140 | 0.9532 | 0.8742 |
| 0.1251 | 10.0 | 550 | 0.0693 | 0.9126 | 0.9558 | 0.8690 |
| 0.1251 | 11.0 | 605 | 0.0687 | 0.9149 | 0.9552 | 0.8732 |
| 0.1251 | 12.0 | 660 | 0.0696 | 0.9124 | 0.9549 | 0.8711 |
| 0.1251 | 13.0 | 715 | 0.0693 | 0.9132 | 0.9564 | 0.8690 |
| 0.1251 | 14.0 | 770 | 0.0680 | 0.9143 | 0.9547 | 0.8732 |
| 0.1251 | 15.0 | 825 | 0.0686 | 0.9127 | 0.9540 | 0.8711 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
