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fg-bert-sustainability-15-1e-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: 0.0893
- F1: 0.9139
- Roc Auc: 0.9527
- 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: 1e-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 | 0.3449 | 0.0 | 0.4999 | 0.0946 |
| No log | 2.0 | 110 | 0.3249 | 0.0 | 0.4999 | 0.0946 |
| No log | 3.0 | 165 | 0.2658 | 0.0755 | 0.5195 | 0.1320 |
| No log | 4.0 | 220 | 0.2092 | 0.4475 | 0.6489 | 0.3077 |
| No log | 5.0 | 275 | 0.1706 | 0.7755 | 0.8312 | 0.6663 |
| No log | 6.0 | 330 | 0.1461 | 0.8566 | 0.8998 | 0.7848 |
| No log | 7.0 | 385 | 0.1290 | 0.8929 | 0.9416 | 0.8430 |
| No log | 8.0 | 440 | 0.1161 | 0.9044 | 0.9463 | 0.8649 |
| No log | 9.0 | 495 | 0.1038 | 0.9111 | 0.9505 | 0.8680 |
| 0.2414 | 10.0 | 550 | 0.0993 | 0.9143 | 0.9523 | 0.8711 |
| 0.2414 | 11.0 | 605 | 0.0957 | 0.9106 | 0.9504 | 0.8669 |
| 0.2414 | 12.0 | 660 | 0.0932 | 0.9123 | 0.9516 | 0.8680 |
| 0.2414 | 13.0 | 715 | 0.0910 | 0.9185 | 0.9561 | 0.8784 |
| 0.2414 | 14.0 | 770 | 0.0901 | 0.9151 | 0.9538 | 0.8742 |
| 0.2414 | 15.0 | 825 | 0.0893 | 0.9139 | 0.9527 | 0.8711 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
