--- base_model: - jondurbin/bagel-dpo-34b-v0.2 - jondurbin/nontoxic-bagel-34b-v0.2 tags: - mergekit - merge license: other license_name: yi-license license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE --- # yi-bagel-2x34b Released January 11, 2024 ![bagel-burger](bagel-burger.png) 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). ## Merge Details ### Merge Method 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). ### Models Merged The following models were included in the merge: * [jondurbin/bagel-dpo-34b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2) * [jondurbin/nontoxic-bagel-34b-v0.2](https://huggingface.co/jondurbin/nontoxic-bagel-34b-v0.2) ## Open LLM Leaderboard Metrics (as of January 11, 2024) | Metric | Value | |-----------------------|-------| | MMLU (5-shot) | 76.60 | | ARC (25-shot) | 72.70 | | HellaSwag (10-shot) | 85.44 | | TruthfulQA (0-shot) | 71.42 | | Winogrande (5-shot) | 82.72 | | GSM8K (5-shot) | 60.73 | | Average | 74.93 | According to the leaderboard description, here are the benchmarks used for the evaluation: - [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. - [AI2 Reasoning Challenge](https://arxiv.org/abs/1803.05457) -ARC- (25-shot) - a set of grade-school science questions. - [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. - [TruthfulQA](https://arxiv.org/abs/2109.07958) (0-shot) - a test to measure a model’s propensity to reproduce falsehoods commonly found online. - [Winogrande](https://arxiv.org/abs/1907.10641) (5-shot) - an adversarial and difficult Winograd benchmark at scale, for commonsense reasoning. - [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. ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: jondurbin/nontoxic-bagel-34b-v0.2 parameters: weight: 0.5 - model: jondurbin/bagel-dpo-34b-v0.2 parameters: weight: 0.5 merge_method: linear dtype: float16 ```