modelscope / modelscope/ms-swift
SFT 和 DPO 两阶段Lora训练,如何训练同一个 adapter
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Description
Checklist / 检查清单
- I have searched existing issues, and this is a new question or discussion topic. / 我已经搜索过现有的 issues,确认这是一个新的问题与讨论。
Question Description / 问题描述
swift rlhf
--rlhf_type dpo
--train_type lora
--model /cpfs_fundata/baolujia.blj/models/Qwen3-8B
--resume_from_checkpoint v0-20260212-195919/checkpoint-4578
--resume_only_model
--ignore_data_skip \
和 直接在合并之后的模型上 lora
swift rlhf
--rlhf_type dpo
--train_type lora
--model v0-20260212-195919/checkpoint-4578-merged
--resume_only_model
--ignore_data_skip \
loss完全不一样
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the loss difference between resuming the LoRA checkpoint with --resume_from_checkpoint and training LoRA on the merged checkpoint using the commands in the issue. Trace how SFT/DPO checkpoint resumption and merged-model loading are handled, and consider the investigation complete when the differing behavior is explained or a reproducible fix is identified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100