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Adding Evaluation Results (#2)

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- Adding Evaluation Results (320c4a13506481a602ce4073bff4c0394ab2b002)


Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>

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  1. README.md +112 -4
README.md CHANGED
@@ -1,12 +1,107 @@
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  ---
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- base_model:
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- - prince-canuma/Ministral-8B-Instruct-2410-HF
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- - prince-canuma/Ministral-8B-Instruct-2410-HF
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  tags:
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  - merge
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  - mergekit
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  - lazymergekit
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  - prince-canuma/Ministral-8B-Instruct-2410-HF
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Ministral-8B-slerp
@@ -59,4 +154,17 @@ pipeline = transformers.pipeline(
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  outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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  print(outputs[0]["generated_text"])
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
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  tags:
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  - merge
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  - mergekit
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  - lazymergekit
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  - prince-canuma/Ministral-8B-Instruct-2410-HF
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+ base_model:
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+ - prince-canuma/Ministral-8B-Instruct-2410-HF
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+ - prince-canuma/Ministral-8B-Instruct-2410-HF
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+ model-index:
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+ - name: Ministral-8B-slerp
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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: 19.61
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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=allknowingroger/Ministral-8B-slerp
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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: 25.2
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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=allknowingroger/Ministral-8B-slerp
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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: 0.0
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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=allknowingroger/Ministral-8B-slerp
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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: 8.28
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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=allknowingroger/Ministral-8B-slerp
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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: 12.4
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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=allknowingroger/Ministral-8B-slerp
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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: 23.55
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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=allknowingroger/Ministral-8B-slerp
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+ name: Open LLM Leaderboard
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  ---
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  # Ministral-8B-slerp
 
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  outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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  print(outputs[0]["generated_text"])
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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_allknowingroger__Ministral-8B-slerp)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |14.84|
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+ |IFEval (0-Shot) |19.61|
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+ |BBH (3-Shot) |25.20|
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+ |MATH Lvl 5 (4-Shot)| 0.00|
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+ |GPQA (0-shot) | 8.28|
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+ |MuSR (0-shot) |12.40|
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+ |MMLU-PRO (5-shot) |23.55|
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+