cf-bert-finetuned-d
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: 0.3203
- F1: 0.6088
- Roc Auc: 0.7421
- Accuracy: 0.3292
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 |
|---|---|---|---|---|---|---|
| 0.3813 | 1.0 | 447 | 0.3823 | 0.4314 | 0.6396 | 0.1646 |
| 0.3274 | 2.0 | 894 | 0.3393 | 0.5559 | 0.7042 | 0.2643 |
| 0.3078 | 3.0 | 1341 | 0.3313 | 0.5781 | 0.7200 | 0.2878 |
| 0.2447 | 4.0 | 1788 | 0.3344 | 0.5888 | 0.7298 | 0.2811 |
| 0.2177 | 5.0 | 2235 | 0.3347 | 0.5859 | 0.7282 | 0.2968 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1