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Eval Results
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Adding Evaluation Results (#1)

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- Adding Evaluation Results (b1ff04d3cb4237971dd5f8c9b9e743a56674eb00)


Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>

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  1. README.md +112 -4
README.md CHANGED
@@ -1,5 +1,4 @@
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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
@@ -9,15 +8,111 @@ language:
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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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- base_model:
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- - VAGOsolutions/SauerkrautLM-v2-14b-SFT
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+