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Adding Evaluation Results (#3)
Browse files- Adding Evaluation Results (c0c110721a71f861c295c52c0520b93294095dec)
Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>
README.md
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language: en
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This is a Hugging Face transformers-compatible conversion of the original dense 2.7B-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found at https://github.com/facebookresearch/fairseq/blob/main/examples/moe_lm/model_card.md.
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language: en
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---
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This is a Hugging Face transformers-compatible conversion of the original dense 2.7B-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found at https://github.com/facebookresearch/fairseq/blob/main/examples/moe_lm/model_card.md.
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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_KoboldAI__fairseq-dense-2.7B)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 33.67 |
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| ARC (25-shot) | 33.79 |
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| HellaSwag (10-shot) | 65.74 |
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| MMLU (5-shot) | 26.44 |
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| TruthfulQA (0-shot) | 34.57 |
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| Winogrande (5-shot) | 63.93 |
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| GSM8K (5-shot) | 0.0 |
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| DROP (3-shot) | 11.24 |
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