--- library_name: transformers tags: - mergekit - merge base_model: - bunnycore/QwQen-3B-LCoT - bunnycore/Qwen-2.5-3b-R1-lora_model-v.1 - Qwen/Qwen2.5-3B-Instruct - bunnycore/Qwen2.5-3B-RP-Thinker-V2 - bunnycore/Qwen-2.5-s1k-R1-lora-v1.1 - bunnycore/Qwen2.5-3B-Model-Stock-v2 model-index: - name: Qwen2.5-3B-Model-Stock-v3.2 results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 63.53 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 26.33 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 37.54 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 4.47 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 6.97 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 25.49 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-3B-Model-Stock-v3.2 name: Open LLM Leaderboard --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) as a base. ### Models Merged The following models were included in the merge: * [bunnycore/QwQen-3B-LCoT](https://huggingface.co/bunnycore/QwQen-3B-LCoT) + [bunnycore/Qwen-2.5-3b-R1-lora_model-v.1](https://huggingface.co/bunnycore/Qwen-2.5-3b-R1-lora_model-v.1) * [bunnycore/Qwen2.5-3B-RP-Thinker-V2](https://huggingface.co/bunnycore/Qwen2.5-3B-RP-Thinker-V2) + [bunnycore/Qwen-2.5-s1k-R1-lora-v1.1](https://huggingface.co/bunnycore/Qwen-2.5-s1k-R1-lora-v1.1) * [bunnycore/Qwen2.5-3B-Model-Stock-v2](https://huggingface.co/bunnycore/Qwen2.5-3B-Model-Stock-v2) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: bunnycore/Qwen2.5-3B-RP-Thinker-V2+bunnycore/Qwen-2.5-s1k-R1-lora-v1.1 - model: bunnycore/Qwen2.5-3B-Model-Stock-v2 - model: bunnycore/QwQen-3B-LCoT+bunnycore/Qwen-2.5-3b-R1-lora_model-v.1 base_model: Qwen/Qwen2.5-3B-Instruct merge_method: model_stock parameters: normalize: true dtype: bfloat16 tokenizer_source: Qwen/Qwen2.5-3B-Instruct ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/bunnycore__Qwen2.5-3B-Model-Stock-v3.2-details) | Metric |Value| |-------------------|----:| |Avg. |27.39| |IFEval (0-Shot) |63.53| |BBH (3-Shot) |26.33| |MATH Lvl 5 (4-Shot)|37.54| |GPQA (0-shot) | 4.47| |MuSR (0-shot) | 6.97| |MMLU-PRO (5-shot) |25.49|