modelscope / modelscope/ms-swift
need ignore_empty_think when training Qwen3.5?
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Description
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- 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
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 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