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Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (595d7d2e84d790145084320c5fe2a2575cc0c58b)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
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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base_model:
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- Qwen/Qwen2.5-14B
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---
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![SauerkrautLM-v2-14b-SFT](https://vago-solutions.ai/wp-content/uploads/2024/11/SauerkrautLM-v2-14b-3.png "SauerkrautLM-v2-14b-SFT")
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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 model to the Open-Source community.
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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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base_model:
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- Qwen/Qwen2.5-14B
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model-index:
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- name: SauerkrautLM-v2-14b-SFT
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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: 69.64
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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-SFT
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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: 45.82
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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-SFT
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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: 29.23
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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-SFT
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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: 11.41
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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-SFT
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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: 11.07
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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-SFT
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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: 46.73
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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-SFT
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name: Open LLM Leaderboard
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---
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![SauerkrautLM-v2-14b-SFT](https://vago-solutions.ai/wp-content/uploads/2024/11/SauerkrautLM-v2-14b-3.png "SauerkrautLM-v2-14b-SFT")
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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 model to the Open-Source community.
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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-SFT)
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| Metric |Value|
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|-------------------|----:|
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|Avg. |35.65|
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|IFEval (0-Shot) |69.64|
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|BBH (3-Shot) |45.82|
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|MATH Lvl 5 (4-Shot)|29.23|
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|GPQA (0-shot) |11.41|
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|MuSR (0-shot) |11.07|
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|MMLU-PRO (5-shot) |46.73|
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