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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 +112 -4
README.md CHANGED
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  ---
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- base_model:
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- - Trappu/Nemo-Picaro-fixed
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- - anthracite-org/magnum-v2-12b
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  tags:
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  - merge
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  - mergekit
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  - lazymergekit
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  - Trappu/Nemo-Picaro-fixed
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  - anthracite-org/magnum-v2-12b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Magnum-Picaro-0.7-v2-12b
@@ -61,4 +156,17 @@ 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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  - Trappu/Nemo-Picaro-fixed
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  - anthracite-org/magnum-v2-12b
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+ base_model:
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+ - Trappu/Nemo-Picaro-fixed
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+ - anthracite-org/magnum-v2-12b
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+ model-index:
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+ - name: Magnum-Picaro-0.7-v2-12b
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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: 30.03
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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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: 35.75
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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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: 4.76
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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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: 9.73
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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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: 19.56
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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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: 28.67
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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=Trappu/Magnum-Picaro-0.7-v2-12b
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+ name: Open LLM Leaderboard
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  ---
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  # Magnum-Picaro-0.7-v2-12b
 
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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_Trappu__Magnum-Picaro-0.7-v2-12b)
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+
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+ | Metric |Value|
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+ |-------------------|----:|
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+ |Avg. |21.42|
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+ |IFEval (0-Shot) |30.03|
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+ |BBH (3-Shot) |35.75|
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+ |MATH Lvl 5 (4-Shot)| 4.76|
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+ |GPQA (0-shot) | 9.73|
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+ |MuSR (0-shot) |19.56|
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+ |MMLU-PRO (5-shot) |28.67|
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+