modelscope / modelscope/ms-swift

need ignore_empty_think when training Qwen3.5?

Open
#8,203 4 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

question stale
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

当训练千问 3.5 纯文本的部分,例如同时使用Qwen3的推理和非推理语料,是否需要加上这个标签来跟原始的基座能力对齐?
--loss_scale ignore_empty_think \

When training the Qwen 3.5 base model on pure text data—where both reasoning corpus and non-reasoning corpus coexist—do we need to add this label to align with the original base model capabilities?

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 with the Qwen 3.5 training setup and the --loss_scale ignore_empty_think option referenced in the issue. Compare mixed reasoning and non-reasoning pure-text data with the original base-model behavior; done means a project-confirmed answer about whether the option is required.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
38/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.