metadata
base_model: mistralai/Mistral-Nemo-Instruct-2407
datasets: allenai/wildjailbreak
tags:
- trl
- sft
- red-teamer-model
- jailbreaking
- generated_from_trainer
This model is a fine-tuned version of mistralai/Mistral-Nemo-Instruct-2407 on the wildjailbreak dataset. Only the adversarial_harmful data types have been used for training.
Uses
This model is intended to be used for red-teaming purposes only. It generates prompts that are likely to evade existing LLMs' content filters based on the user's input.
→ The HarmBench evaluation will be released soon.
Training Hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Results
| Epoch | Step | Validation Loss | Training Loss |
|---|---|---|---|
| 0.0982 | 20 | 1.2933 | 1.3425 |
| 0.1965 | 40 | 1.1966 | 1.2067 |
| 0.2947 | 60 | 1.1594 | 1.1544 |
| 0.3930 | 80 | 1.1386 | 1.1427 |
| 0.4912 | 100 | 1.1259 | 1.1235 |
| 0.5895 | 120 | 1.1179 | 1.1167 |
| 0.6877 | 140 | 1.1129 | 1.1153 |
| 0.7860 | 160 | 1.1098 | 1.1118 |
| 0.8842 | 180 | 1.1086 | 1.1112 |
| 0.9825 | 200 | 1.1083 | 1.1113 |