nli-MiniLM2-L6-H768-trustairlab-jailbreak-augmented
This model is a fine-tuned version of cross-encoder/nli-MiniLM2-L6-H768 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1679
- Accuracy: 0.9490
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5366 | 1.0 | 4240 | 0.2266 | 0.9145 |
| 0.3510 | 2.0 | 8480 | 0.1958 | 0.9325 |
| 0.1047 | 3.0 | 12720 | 0.2034 | 0.9328 |
| 0.1698 | 4.0 | 16960 | 0.1680 | 0.9491 |
| 0.2465 | 5.0 | 21200 | 0.1742 | 0.9483 |
| 0.1220 | 6.0 | 25440 | 0.1811 | 0.9515 |
| 0.0504 | 7.0 | 29680 | 0.1781 | 0.9529 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2