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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 +122 -6
README.md CHANGED
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  ---
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- license: apache-2.0
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- base_model:
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- - mistralai/Mistral-7B-v0.1
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- datasets:
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- - nvidia/OpenMathInstruct-1
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  language:
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  - en
 
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  tags:
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  - nvidia
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  - code
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  - math
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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@@ -118,4 +221,17 @@ If you find our work useful, please consider citing us!
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  year = {2024},
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  journal = {arXiv preprint arXiv: Arxiv-2402.10176}
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  }
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
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  language:
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  - en
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+ license: apache-2.0
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  tags:
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  - nvidia
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  - code
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  - math
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+ datasets:
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+ - nvidia/OpenMathInstruct-1
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+ base_model:
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+ - mistralai/Mistral-7B-v0.1
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+ model-index:
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+ - name: OpenMath-Mistral-7B-v0.1-hf
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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: AI2 Reasoning Challenge (25-Shot)
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+ type: ai2_arc
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+ config: ARC-Challenge
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+ split: test
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+ args:
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+ num_few_shot: 25
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+ metrics:
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+ - type: acc_norm
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+ value: 59.39
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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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: HellaSwag (10-Shot)
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+ type: hellaswag
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+ split: validation
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+ args:
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+ num_few_shot: 10
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+ metrics:
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+ - type: acc_norm
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+ value: 81.78
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+ name: normalized accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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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 (5-Shot)
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+ type: cais/mmlu
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+ config: all
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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: 59.34
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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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: TruthfulQA (0-shot)
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+ type: truthful_qa
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+ config: multiple_choice
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+ split: validation
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+ args:
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+ num_few_shot: 0
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+ metrics:
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+ - type: mc2
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+ value: 46.13
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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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: Winogrande (5-shot)
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+ type: winogrande
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+ config: winogrande_xl
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+ split: validation
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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: 77.27
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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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: GSM8k (5-shot)
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+ type: gsm8k
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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: 0.08
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+ name: accuracy
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=nvidia/OpenMath-Mistral-7B-v0.1-hf
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+ name: Open LLM Leaderboard
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  ---
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  year = {2024},
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  journal = {arXiv preprint arXiv: Arxiv-2402.10176}
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  }
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+ ```
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_nvidia__OpenMath-Mistral-7B-v0.1-hf)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |54.00|
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+ |AI2 Reasoning Challenge (25-Shot)|59.39|
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+ |HellaSwag (10-Shot) |81.78|
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+ |MMLU (5-Shot) |59.34|
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+ |TruthfulQA (0-shot) |46.13|
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+ |Winogrande (5-shot) |77.27|
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+ |GSM8k (5-shot) | 0.08|
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+