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---
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base_model:
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- Qwen/Qwen2.5-14B-Instruct
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- Qwen/Qwen2.5-14B
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library_name: transformers
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tags:
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- mergekit
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- merge
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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---
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# qwenselfbaseinstruct
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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Re-injected base model into instruct model in the intermediate layers while keeping input and output layers the same (sophosympatheia gradient).
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While this did degrade the overall score of the model compared to instruct in EQ-bench testing (76.9195 down to 73.8068),
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it removed its issue with misspelling some of the emotion responses and remains notably higher than the base model
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(60.1027 but without any syntax errors).
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It did throw in one non-mispelled "didn't match reference" syntax error, I presume it replaced the emotion entirely or used a similar grammatically correct one.
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Looking at this as research evidence, it seems like the instruct model picked up something hurting the spelling occasionally specifically in the intermediate layers?
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I don't know if there's any other gain from this merge compared to using one or both components, this was for curiosity.
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Might still be useful as more-compact merge materials if you wanted both base and instruct anyway.
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
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* [Qwen/Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2.5-14B)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: Qwen/Qwen2.5-14B
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merge_method: slerp
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base_model: Qwen/Qwen2.5-14B-Instruct
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parameters:
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t:
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- value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
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dtype: bfloat16
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```
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