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README.md
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![bagel-burger](bagel-burger.png)
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). For more information, kindly refer to the model cards from jondurbin linked in
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## Merge Details
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### Merge Method
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* [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2)
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* [jondurbin/nontoxic-bagel-34b-v0.2](https://huggingface.co/jondurbin/nontoxic-bagel-34b-v0.2)
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### Configuration
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The following YAML configuration was used to produce this model:
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![bagel-burger](bagel-burger.png)
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). For more information, kindly refer to the model cards from jondurbin linked in the section below. This model debuted in the [leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) at rank #4 (January 11, 2024).
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## Merge Details
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### Merge Method
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* [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2)
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* [jondurbin/nontoxic-bagel-34b-v0.2](https://huggingface.co/jondurbin/nontoxic-bagel-34b-v0.2)
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## Open LLM Leaderboard Metrics (as of January 11, 2024)
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| Metric | Value |
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| MMLU (5-shot) | 76.60 |
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| ARC (25-shot) | 72.70 |
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| HellaSwag (10-shot) | 85.44 |
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| TruthfulQA (0-shot) | 71.42 |
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| Winogrande (5-shot) | 82.72 |
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| GSM8K (5-shot) | 60.73 |
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| Average | 74.93 |
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According to the leaderboard description, here are the benchmarks used for the evaluation:
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- [MMLU](https://arxiv.org/abs/2009.03300) (5-shot) - a test to measure a text model’s multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more.
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- [AI2 Reasoning Challenge](https://arxiv.org/abs/1803.05457) -ARC- (25-shot) - a set of grade-school science questions.
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- [HellaSwag](https://arxiv.org/abs/1905.07830) (10-shot) - a test of commonsense inference, which is easy for humans (~95%) but challenging for SOTA models.
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- [TruthfulQA](https://arxiv.org/abs/2109.07958) (0-shot) - a test to measure a model’s propensity to reproduce falsehoods commonly found online.
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- [Winogrande](https://arxiv.org/abs/1907.10641) (5-shot) - an adversarial and difficult Winograd benchmark at scale, for commonsense reasoning.
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- [GSM8k](https://arxiv.org/abs/2110.14168) (5-shot) - diverse grade school math word problems to measure a model's ability to solve multi-step mathematical reasoning problems.
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### Configuration
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The following YAML configuration was used to produce this model:
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