cf-robert-finetuned-r
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3111
- F1: 0.6155
- Roc Auc: 0.7474
- Accuracy: 0.3315
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 |
|---|---|---|---|---|---|---|
| 0.3819 | 1.0 | 447 | 0.3901 | 0.4253 | 0.6370 | 0.1624 |
| 0.3286 | 2.0 | 894 | 0.3428 | 0.5409 | 0.6953 | 0.2665 |
| 0.3108 | 3.0 | 1341 | 0.3255 | 0.5921 | 0.7283 | 0.3102 |
| 0.2659 | 4.0 | 1788 | 0.3254 | 0.6128 | 0.7431 | 0.3180 |
| 0.2347 | 5.0 | 2235 | 0.3251 | 0.6184 | 0.7469 | 0.3236 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1