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--- |
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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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base_model: |
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- bunnycore/FuseQwQen-7B |
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- bunnycore/Qwen-2.5-7B-R1-Stock |
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- bunnycore/Qwen-2.5-7B-Deep-Stock-v1 |
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- Qwen/Qwen2.5-7B-Instruct |
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model-index: |
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- name: Qwen-2.5-7B-Deep-Stock-v4 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 77.53 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 35.91 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 48.94 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 6.71 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 10.39 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 37.13 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen-2.5-7B-Deep-Stock-v4 |
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name: Open LLM Leaderboard |
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--- |
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# merge |
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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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## Merge Details |
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### Merge Method |
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This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* [bunnycore/FuseQwQen-7B](https://huggingface.co/bunnycore/FuseQwQen-7B) |
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* [bunnycore/Qwen-2.5-7B-R1-Stock](https://huggingface.co/bunnycore/Qwen-2.5-7B-R1-Stock) |
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* [bunnycore/Qwen-2.5-7B-Deep-Stock-v1](https://huggingface.co/bunnycore/Qwen-2.5-7B-Deep-Stock-v1) |
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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: bunnycore/FuseQwQen-7B |
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parameters: |
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weight: 0.5 |
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- model: bunnycore/Qwen-2.5-7B-Deep-Stock-v1 |
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- model: bunnycore/Qwen-2.5-7B-R1-Stock |
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- model: Qwen/Qwen2.5-7B-Instruct |
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base_model: Qwen/Qwen2.5-7B-Instruct |
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merge_method: model_stock |
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parameters: |
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dtype: bfloat16 |
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tokenizer_source: Qwen/Qwen2.5-7B-Instruct |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/bunnycore__Qwen-2.5-7B-Deep-Stock-v4-details) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |36.10| |
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|IFEval (0-Shot) |77.53| |
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|BBH (3-Shot) |35.91| |
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|MATH Lvl 5 (4-Shot)|48.94| |
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|GPQA (0-shot) | 6.71| |
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|MuSR (0-shot) |10.39| |
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|MMLU-PRO (5-shot) |37.13| |
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