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Adding Evaluation Results

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This 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

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  1. README.md +113 -5
README.md CHANGED
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  ---
 
 
 
 
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  base_model:
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  - DreadPoor/Spei_Meridiem-8B-model_stock
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  - unsloth/Meta-Llama-3.1-8B
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  - DreadPoor/Heart_Stolen1.1-8B-Model_Stock
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  - DreadPoor/Aspire1.1-8B-model_stock
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- library_name: transformers
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- tags:
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- - mergekit
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- - merge
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # merge
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@@ -52,3 +146,17 @@ parameters:
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  dtype: float32
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  out_dtype: bfloat16
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ library_name: transformers
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+ tags:
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+ - mergekit
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+ - merge
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  base_model:
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  - DreadPoor/Spei_Meridiem-8B-model_stock
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  - unsloth/Meta-Llama-3.1-8B
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  - DreadPoor/Heart_Stolen1.1-8B-Model_Stock
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  - DreadPoor/Aspire1.1-8B-model_stock
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+ model-index:
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+ - name: L3.1-Promissum_Mane-8B-Della-calc
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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: 54.42
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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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: 35.55
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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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: 6.6
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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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: 12.81
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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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: 31.13
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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=djuna/L3.1-Promissum_Mane-8B-Della-calc
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+ name: Open LLM Leaderboard
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  ---
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  # merge
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  dtype: float32
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  out_dtype: bfloat16
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  ```
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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_djuna__L3.1-Promissum_Mane-8B-Della-calc)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |23.42|
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+ |IFEval (0-Shot) |54.42|
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+ |BBH (3-Shot) |35.55|
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+ |MATH Lvl 5 (4-Shot)| 0.00|
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+ |GPQA (0-shot) | 6.60|
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+ |MuSR (0-shot) |12.81|
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+ |MMLU-PRO (5-shot) |31.13|
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+