Adding Evaluation Results

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  1. README.md +14 -1
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@@ -77,4 +77,17 @@ The attention mechanism in a transformer model is designed to capture global dep
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  The finetuning scripts will be available in our [RAIL Github Repository](https://github.com/vmware-labs/research-and-development-artificial-intelligence-lab/tree/main/instruction-tuning)
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  ## Evaluation
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- <B>TODO</B>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  The finetuning scripts will be available in our [RAIL Github Repository](https://github.com/vmware-labs/research-and-development-artificial-intelligence-lab/tree/main/instruction-tuning)
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  ## Evaluation
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+ <B>TODO</B>
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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_VMware__open-llama-7b-open-instruct)
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+
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+ | Metric | Value |
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+ |-----------------------|---------------------------|
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+ | Avg. | 40.9 |
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+ | ARC (25-shot) | 49.74 |
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+ | HellaSwag (10-shot) | 73.67 |
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+ | MMLU (5-shot) | 31.52 |
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+ | TruthfulQA (0-shot) | 34.65 |
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+ | Winogrande (5-shot) | 65.43 |
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+ | GSM8K (5-shot) | 0.53 |
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+ | DROP (3-shot) | 30.75 |