leaderboard-pr-bot
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Adding Evaluation Results
Browse filesThis is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
README.md
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---
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license: apache-2.0
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language:
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- de
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- en
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- nl
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- ar
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- es
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tags:
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- spectrum
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- sft
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- dpo
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datasets:
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- VAGOsolutions/SauerkrautLM-Fermented-GER-DPO
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- VAGOsolutions/SauerkrautLM-Fermented-Irrelevance-GER-DPO
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---
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@@ -137,4 +232,17 @@ If you are interested in customized LLMs for business applications, please get i
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We are also keenly seeking support and investment for our startup, VAGO solutions where we continuously advance the development of robust language models designed to address a diverse range of purposes and requirements. If the prospect of collaboratively navigating future challenges excites you, we warmly invite you to reach out to us at [VAGO solutions](https://vago-solutions.ai)
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## Acknowledgement
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-
Many thanks to [Qwen](https://huggingface.co/Qwen) for providing such a valuable base model, and to our community for their continued support and engagement.
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---
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language:
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- de
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- en
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- nl
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- ar
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- es
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license: apache-2.0
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tags:
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- spectrum
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- sft
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- dpo
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base_model:
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- VAGOsolutions/SauerkrautLM-v2-14b-SFT
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datasets:
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- VAGOsolutions/SauerkrautLM-Fermented-GER-DPO
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- VAGOsolutions/SauerkrautLM-Fermented-Irrelevance-GER-DPO
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model-index:
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- name: SauerkrautLM-v2-14b-DPO
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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: 74.12
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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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: 50.93
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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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: 27.34
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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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: 9.28
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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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: 13.78
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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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: 45.75
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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=VAGOsolutions/SauerkrautLM-v2-14b-DPO
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name: Open LLM Leaderboard
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---
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We are also keenly seeking support and investment for our startup, VAGO solutions where we continuously advance the development of robust language models designed to address a diverse range of purposes and requirements. If the prospect of collaboratively navigating future challenges excites you, we warmly invite you to reach out to us at [VAGO solutions](https://vago-solutions.ai)
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## Acknowledgement
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Many thanks to [Qwen](https://huggingface.co/Qwen) for providing such a valuable base model, and to our community for their continued support and engagement.
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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_VAGOsolutions__SauerkrautLM-v2-14b-DPO)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |36.87|
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|IFEval (0-Shot) |74.12|
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|BBH (3-Shot) |50.93|
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|MATH Lvl 5 (4-Shot)|27.34|
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|GPQA (0-shot) | 9.28|
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|MuSR (0-shot) |13.78|
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|MMLU-PRO (5-shot) |45.75|
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