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bert-eval
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2288
- F1: 0.7837
- Roc Auc: 0.8490
- Accuracy: 0.3137
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4067 | 1.0 | 751 | 0.2930 | 0.7145 | 0.7911 | 0.2188 |
| 0.2483 | 2.0 | 1502 | 0.2528 | 0.7493 | 0.8167 | 0.2777 |
| 0.1993 | 3.0 | 2253 | 0.2323 | 0.7772 | 0.8406 | 0.3067 |
| 0.1468 | 4.0 | 3004 | 0.2288 | 0.7837 | 0.8490 | 0.3137 |
| 0.1238 | 5.0 | 3755 | 0.2287 | 0.7837 | 0.8509 | 0.3217 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
