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  ---
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- license: other
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  language:
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  - zh
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  - en
 
 
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  datasets:
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  - thomas-yanxin/MT-SFT-ShareGPT
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- base_model: Qwen2-1.5B
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  The main purpose of this model is to validate the usability of [thomas-yanxin/MT-SFT-ShareGPT](https://huggingface.co/datasets/thomas-yanxin/MT-SFT-ShareGPT), i.e., the quality of the data is all you need. We found that when we meticulously extract the data through a better data governance approach, the corresponding model results can be vastly improved, even if only through SFT.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
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  language:
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  - zh
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  - en
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+ license: other
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+ base_model: Qwen2-1.5B
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  datasets:
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  - thomas-yanxin/MT-SFT-ShareGPT
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+ model-index:
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+ - name: XinYuan-Qwen2-1_5B
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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: 29.86
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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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: 12.13
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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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: 6.12
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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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: 2.68
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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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: 2.62
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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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: 15.08
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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=thomas-yanxin/XinYuan-Qwen2-1_5B
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+ name: Open LLM Leaderboard
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  ---
105
 
106
  The main purpose of this model is to validate the usability of [thomas-yanxin/MT-SFT-ShareGPT](https://huggingface.co/datasets/thomas-yanxin/MT-SFT-ShareGPT), i.e., the quality of the data is all you need. We found that when we meticulously extract the data through a better data governance approach, the corresponding model results can be vastly improved, even if only through SFT.
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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/details_thomas-yanxin__XinYuan-Qwen2-1_5B)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |11.41|
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+ |IFEval (0-Shot) |29.86|
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+ |BBH (3-Shot) |12.13|
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+ |MATH Lvl 5 (4-Shot)| 6.12|
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+ |GPQA (0-shot) | 2.68|
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+ |MuSR (0-shot) | 2.62|
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+ |MMLU-PRO (5-shot) |15.08|
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+