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--- |
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base_model: |
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- jondurbin/bagel-dpo-34b-v0.2 |
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- jondurbin/nontoxic-bagel-34b-v0.2 |
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tags: |
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- mergekit |
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- merge |
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license: other |
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license_name: yi-license |
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license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE |
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--- |
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# yi-bagel-2x34b |
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Released January 11, 2024 |
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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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This model is an expertimental merge using the [linear](https://arxiv.org/abs/2203.05482) merge method. This is to assess the degree of which the DPO has an effect, in terms of censoring, as used in [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2). |
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### Models Merged |
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The following models were included in the merge: |
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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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|-----------------------|-------| |
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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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```yaml |
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models: |
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- model: jondurbin/nontoxic-bagel-34b-v0.2 |
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parameters: |
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weight: 0.5 |
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- model: jondurbin/bagel-dpo-34b-v0.2 |
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parameters: |
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weight: 0.5 |
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merge_method: linear |
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dtype: float16 |
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``` |
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## Further Information |
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For additional information or inquiries about yi-bagel-2x34b, please contact the developer through email: [email protected]. |
