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Model: harborwater/open-llama-3b-everything-v2 Source: Original Platform
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README.md
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---
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license: apache-2.0
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datasets:
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- totally-not-an-llm/EverythingLM-data-V2-sharegpt
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language:
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- en
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library_name: transformers
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---
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Trained on 3 epochs of the `totally-not-an-llm/EverythingLM-data-V2-sharegpt` dataset.
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```
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### HUMAN:
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{prompt}
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### RESPONSE:
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<leave a newline for the model to answer>
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```
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note: Changed a few of the finetuning parameters this time around. I have no idea if its any good but Feel free to give it a try!
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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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_harborwater__open-llama-3b-everything-v2)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 36.29 |
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| ARC (25-shot) | 42.83 |
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| HellaSwag (10-shot) | 73.28 |
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| MMLU (5-shot) | 26.87 |
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| TruthfulQA (0-shot) | 37.26 |
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| Winogrande (5-shot) | 66.61 |
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| GSM8K (5-shot) | 1.59 |
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| DROP (3-shot) | 5.61 |
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