cf-bert-finetuned-h
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: 0.3081
- F1: 0.6059
- Roc Auc: 0.7437
- Accuracy: 0.3386
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 |
|---|---|---|---|---|---|---|
| 0.3625 | 1.0 | 445 | 0.3605 | 0.3984 | 0.6252 | 0.1475 |
| 0.3177 | 2.0 | 890 | 0.3195 | 0.5400 | 0.6955 | 0.2680 |
| 0.295 | 3.0 | 1335 | 0.3111 | 0.6011 | 0.7360 | 0.3266 |
| 0.2625 | 4.0 | 1780 | 0.3134 | 0.6027 | 0.7402 | 0.3255 |
| 0.2366 | 5.0 | 2225 | 0.3161 | 0.6006 | 0.7398 | 0.3232 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1