From ed54e415be88340a341273f4451adfdafe6934b7 Mon Sep 17 00:00:00 2001 From: Yu Meng Date: Thu, 22 Aug 2024 16:17:43 -0400 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2423eca..1f78c2e 100644 --- a/README.md +++ b/README.md @@ -70,7 +70,7 @@ The [CPO_SIMPO](https://github.com/fe1ixxu/CPO_SIMPO/tree/main) repository did p ## Released Models ### Gemma -We release the following two models that are built on top of the strong [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) model by training DPO and SimPO on the on-policy dataset [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm). For GSM and MMLU, we use the [EvalZero](https://github.com/yuchenlin/ZeroEval) repository which aims to evaluate instruction-tuned LLMs (i.e., chat models instead of base models) for their zero-shot performance on reasoning and knowledge heavy tasks. More results on [WildBench](https://huggingface.co/spaces/allenai/WildBench) are coming soon. +We release the following two models that are built on top of the strong [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) model by training DPO and SimPO on the on-policy dataset [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm). For GSM and MMLU, we use the [ZeroEval](https://github.com/yuchenlin/ZeroEval) repository which aims to evaluate instruction-tuned LLMs (i.e., chat models instead of base models) for their zero-shot performance on reasoning and knowledge heavy tasks. More results on [WildBench](https://huggingface.co/spaces/allenai/WildBench) are coming soon. | models | AE2 LC | AE2 WR | AE2 Length | AH | AH Length | GSM | GSM Length | MMLU | MMLU Length | |-----------------------------------|:------:|:------:|:----------:|:----:|:---------:|:----:|:----------:|:----:|:-----------:|