SimNPO-Unlearned Model on Task "WMDP"

Model Details

• Unlearning:
  • Task: 🤗datasets/cais/wmdp
  • Method: SimNPO
• Origin Model: 🤗HuggingFaceH4/zephyr-7b-beta
• Code Base: github.com/OPTML-Group/Unlearn-Simple
• Research Paper: "Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning"

Unlearning Algorithm

This model uses the SimNPO unlearning algorithm with the following optimization objective: ℓSimNPO​(θ)=E(x,y)∈Df​​[−β2​logσ(−∣y∣β​logπθ​(y∣x)−γ)]+λE(x,y)∈Dr​​[−logπθ​(y∣x)] Unlearning hyper-parameters:

• Learning Rate: 4e-6
• beta: 5.5
• lambda: 5.0
• gamma: 0.0

Loading the Model

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("OPTML-Group/SimNPO-WMDP-zephyr-7b-beta", use_flash_attention_2=True, torch_dtype=torch.bfloat16, trust_remote_code=True)

Evaluation Results

Citation

If you use this model in your research, please cite:

@article{fan2024simplicity,
 title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning},
 author={Fan, Chongyu and Liu, Jiancheng and Lin, Licong and Jia, Jinghan and Zhang, Ruiqi and Mei, Song and Liu, Sijia},
 journal={arXiv preprint arXiv:2410.07163},
 year={2024}
}

Reporting Issues

Reporting issues with the model: github.com/OPTML-Group/Unlearn-Simple

Base model