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fg-bert-sustainability-15-2.2e-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: 0.0692
- F1: 0.9101
- Roc Auc: 0.9480
- Accuracy: 0.8669
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: 2.2e-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 | 0.3161 | 0.0 | 0.5 | 0.0956 |
| No log | 2.0 | 110 | 0.1855 | 0.6907 | 0.7781 | 0.5530 |
| No log | 3.0 | 165 | 0.1222 | 0.8989 | 0.9428 | 0.8472 |
| No log | 4.0 | 220 | 0.0961 | 0.9056 | 0.9451 | 0.8649 |
| No log | 5.0 | 275 | 0.0861 | 0.9089 | 0.9469 | 0.8659 |
| No log | 6.0 | 330 | 0.0789 | 0.9107 | 0.9486 | 0.8690 |
| No log | 7.0 | 385 | 0.0775 | 0.9036 | 0.9472 | 0.8597 |
| No log | 8.0 | 440 | 0.0736 | 0.9046 | 0.9473 | 0.8617 |
| No log | 9.0 | 495 | 0.0726 | 0.9101 | 0.9480 | 0.8680 |
| 0.1401 | 10.0 | 550 | 0.0707 | 0.9084 | 0.9469 | 0.8628 |
| 0.1401 | 11.0 | 605 | 0.0714 | 0.9087 | 0.9483 | 0.8617 |
| 0.1401 | 12.0 | 660 | 0.0689 | 0.9128 | 0.9516 | 0.8711 |
| 0.1401 | 13.0 | 715 | 0.0689 | 0.9112 | 0.9510 | 0.8690 |
| 0.1401 | 14.0 | 770 | 0.0695 | 0.9096 | 0.9480 | 0.8669 |
| 0.1401 | 15.0 | 825 | 0.0692 | 0.9101 | 0.9480 | 0.8669 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
