Model Stock: All we need is just a few fine-tuned models
Paper
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2403.19522
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Published
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13
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the Model Stock merge method using Qwen/Qwen2.5-7B-Instruct as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: bunnycore/FuseQwQen-7B
parameters:
weight: 0.5
- model: bunnycore/Qwen-2.5-7B-Deep-Stock-v1
- model: bunnycore/Qwen-2.5-7B-R1-Stock
- model: Qwen/Qwen2.5-7B-Instruct
base_model: Qwen/Qwen2.5-7B-Instruct
merge_method: model_stock
parameters:
dtype: bfloat16
tokenizer_source: Qwen/Qwen2.5-7B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 36.10 |
| IFEval (0-Shot) | 77.53 |
| BBH (3-Shot) | 35.91 |
| MATH Lvl 5 (4-Shot) | 48.94 |
| GPQA (0-shot) | 6.71 |
| MuSR (0-shot) | 10.39 |
| MMLU-PRO (5-shot) | 37.13 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard77.530
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.910
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard48.940
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.710
- acc_norm on MuSR (0-shot)Open LLM Leaderboard10.390
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard37.130