[Chat] Rlhf support SimPO #5850
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TongLi3701
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Jun 25, 2024
TongLi3701
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Jun 30, 2024
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| ### Alternative Option For RLHF: Odds Ratio Preference Optimization | ||
| We support the method introduced in the paper [ORPO: Monolithic Preference Optimization without Reference Model](https://arxiv.org/abs/2403.07691) (ORPO). Which is a reference model free aligment method that mixes the SFT loss with a reinforcement learning loss that uses odds ratio as the implicit reward to enhance training stability and efficiency. Simply set the flag to disable the use of the reference model, set the reward target margin and enable length normalization in the DPO training script. To use ORPO in alignment, use the [train_orpo.sh](./examples/training_scripts/train_orpo.sh) script, You can set the value for `lambda` (which determine how strongly the reinforcement learning loss affect the training) but it is optional. | ||
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| #### ORPO Result | ||
| <p align="center"> | ||
| <img width="1000" alt="image" src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chat/ORPO_margin.png"> | ||
| </p> |
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Please also add hardware requirement for SimPO and ORPO. Ideally ORPO should be more efficient and compute friendly.
To align with the overall style, you can represent them into a table as it described for PPO.
In addition, as we already support LORA in our training pipeline, please also provide hardware requirements with LORA for each method. Thanks.
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