cf-robert-finetuned1
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4838
- F1: 0.5790
- Roc Auc: 0.7124
- Accuracy: 0.3218
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 |
|---|---|---|---|---|---|---|
| 0.4218 | 1.0 | 434 | 0.4404 | 0.5035 | 0.6667 | 0.2691 |
| 0.3743 | 2.0 | 868 | 0.4277 | 0.5666 | 0.7020 | 0.3256 |
| 0.3538 | 3.0 | 1302 | 0.4413 | 0.5702 | 0.7048 | 0.3314 |
| 0.2671 | 4.0 | 1736 | 0.4460 | 0.5907 | 0.7178 | 0.3337 |
| 0.2921 | 5.0 | 2170 | 0.4670 | 0.5932 | 0.7205 | 0.3256 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1