modelscope / modelscope/ms-swift

SFT 和 DPO 两阶段Lora训练,如何训练同一个 adapter

Open
#8,047 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

question
Dominant language
Python
Stars
15.7k
Forks
1.7k
Avg merge
1d 16h
Merged PRs (30d)
136

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

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. 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

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.