SkyMath: Technical Report

Liu Yang; Haihua Yang; Wenjun Cheng; Lei Lin; Chenxia Li; Yifu Chen; Lunan Liu; Jianfei Pan; Tianwen Wei; Biye Li; Liang Zhao; Lijie Wang; Bo Zhu; Guoliang Li; Xuejie Wu; Xilin Luo; Rui Hu

SkyMath: Technical Report

Computation and Language 2023-10-27 v2 Artificial Intelligence

Authors: Liu Yang , Haihua Yang , Wenjun Cheng , Lei Lin , Chenxia Li , Yifu Chen , Lunan Liu , Jianfei Pan , Tianwen Wei , Biye Li , Liang Zhao , Lijie Wang , Bo Zhu , Guoliang Li , Xuejie Wu , Xilin Luo , Rui Hu

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Abstract

Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning. In this work, we present SkyMath, a large language model for mathematics with 13 billion parameters. By applying self-compare fine-tuning, we have enhanced mathematical reasoning abilities of Skywork-13B-Base remarkably. On GSM8K, SkyMath outperforms all known open-source models of similar size and has established a new SOTA performance.

Keywords

large language model large language model evaluation code generation

Cite

@article{arxiv.2310.16713,
  title  = {SkyMath: Technical Report},
  author = {Liu Yang and Haihua Yang and Wenjun Cheng and Lei Lin and Chenxia Li and Yifu Chen and Lunan Liu and Jianfei Pan and Tianwen Wei and Biye Li and Liang Zhao and Lijie Wang and Bo Zhu and Guoliang Li and Xuejie Wu and Xilin Luo and Rui Hu},
  journal= {arXiv preprint arXiv:2310.16713},
  year   = {2023}
}

SkyMath: Technical Report

Abstract

Keywords

Cite

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