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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 +14 -1
README.md CHANGED
@@ -109,4 +109,17 @@ cd lm-evaluation-harness
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  ## Contact Us
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  ### Why Upstage LLM?
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- - [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. As of August 1st, our 70B model has reached the top spot in openLLM rankings, marking itself as the current leading performer globally. Recognizing the immense potential in implementing private LLM to actual businesses, we invite you to easily apply private LLM and fine-tune it with your own data. For a seamless and tailored solution, please do not hesitate to reach out to us. ► [click here to contact](https://www.upstage.ai/private-llm?utm_source=huggingface&utm_medium=link&utm_campaign=privatellm)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Contact Us
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  ### Why Upstage LLM?
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+ - [Upstage](https://en.upstage.ai)'s LLM research has yielded remarkable results. As of August 1st, our 70B model has reached the top spot in openLLM rankings, marking itself as the current leading performer globally. Recognizing the immense potential in implementing private LLM to actual businesses, we invite you to easily apply private LLM and fine-tune it with your own data. For a seamless and tailored solution, please do not hesitate to reach out to us. ► [click here to contact](https://www.upstage.ai/private-llm?utm_source=huggingface&utm_medium=link&utm_campaign=privatellm)
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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_upstage__Llama-2-70b-instruct)
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+
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+ | Metric | Value |
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+ |-----------------------|---------------------------|
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+ | Avg. | 66.1 |
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+ | ARC (25-shot) | 70.9 |
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+ | HellaSwag (10-shot) | 87.48 |
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+ | MMLU (5-shot) | 69.8 |
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+ | TruthfulQA (0-shot) | 60.97 |
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+ | Winogrande (5-shot) | 82.87 |
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+ | GSM8K (5-shot) | 32.22 |
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+ | DROP (3-shot) | 58.42 |