results
This model is a fine-tuned version of bert-base-uncased on an [SalKhan12/prompt-safety-dataset] dataset. It achieves the following results on the evaluation set:
- Loss: 0.1155
- Accuracy: 0.9631
- Precision: 0.9498
- Recall: 0.9545
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.1415 | 1.0 | 3709 | 0.1212 | 0.9560 | 0.9297 | 0.9575 |
| 0.0869 | 2.0 | 7418 | 0.1154 | 0.9644 | 0.9526 | 0.9546 |
| 0.0294 | 3.0 | 11127 | 0.1431 | 0.9648 | 0.9523 | 0.9561 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2