开源实习-金逸-sequence_classification/vera模型微调 #1989
Open
+10,087
−11
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
issue地址:https://gitee.com/mindspore/community/issues/IAN0OJ
任务开始发现vera微调方式并未实现，因此本次pr首先实现了vera微调，再利用实现的vera进行finetuning，finetuning和示例的对比如下:
首先对比模型微调参数占比:
torch:
mindnlp:
再对比微调结果:
torch:
mindnlp:
两者基本相同