cf-bert-finetuned1
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2369
- F1: 0.4601
- Roc Auc: 0.6770
- Accuracy: 0.3990
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2436 | 1.0 | 478 | 0.2402 | 0.1822 | 0.5501 | 0.1384 |
| 0.2042 | 2.0 | 956 | 0.2209 | 0.3900 | 0.6295 | 0.2956 |
| 0.1708 | 3.0 | 1434 | 0.2189 | 0.4649 | 0.6706 | 0.3784 |
| 0.165 | 4.0 | 1912 | 0.2207 | 0.4900 | 0.6877 | 0.4119 |
| 0.1439 | 5.0 | 2390 | 0.2307 | 0.4951 | 0.6945 | 0.4287 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1