--- base_model: - FreedomIntelligence/HuatuoGPT-o1-8B - Skywork/Skywork-o1-Open-Llama-3.1-8B library_name: transformers pipeline_tag: text-generation tags: - mergekit - merge license: llama3.1 model-index: - name: HuatuoSkywork-o1-Llama-3.1-8B results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: wis-k/instruction-following-eval split: train args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 39.61 name: averaged accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: SaylorTwift/bbh split: test args: num_few_shot: 3 metrics: - type: acc_norm value: 28.33 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: lighteval/MATH-Hard split: test args: num_few_shot: 4 metrics: - type: exact_match value: 33.99 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa split: train args: num_few_shot: 0 metrics: - type: acc_norm value: 5.7 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B 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: 11.12 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B 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: 23.28 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B name: Open LLM Leaderboard --- # HuatuoSkywork-o1-Llama-3.1-8B This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). This is an experiment to see what happens when two o1-inspired models are merged. The result achieves an unexpectedly high MATH Lvl 5 benchmark of 33.99%. Built with Llama. ## Merge Details ### Merge Method This model was merged using the SLERP merge method. ### Models Merged The following models were included in the merge: * [FreedomIntelligence/HuatuoGPT-o1-8B](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-8B) * [Skywork/Skywork-o1-Open-Llama-3.1-8B](https://huggingface.co/Skywork/Skywork-o1-Open-Llama-3.1-8B) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: Skywork/Skywork-o1-Open-Llama-3.1-8B - model: FreedomIntelligence/HuatuoGPT-o1-8B merge_method: slerp base_model: Skywork/Skywork-o1-Open-Llama-3.1-8B parameters: t: - value: 0.5 dtype: bfloat16 ``` # [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/grimjim__HuatuoSkywork-o1-Llama-3.1-8B-details)! Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=grimjim%2FHuatuoSkywork-o1-Llama-3.1-8B&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)! | Metric |Value (%)| |-------------------|--------:| |**Average** | 23.67| |IFEval (0-Shot) | 39.61| |BBH (3-Shot) | 28.33| |MATH Lvl 5 (4-Shot)| 33.99| |GPQA (0-shot) | 5.70| |MuSR (0-shot) | 11.12| |MMLU-PRO (5-shot) | 23.28|