learn.ifs.name

Self-Instruct: Aligning Language Models with Self-Generated Instructions

Wang et al., 2023, Self-Instruct (Proceedings of the 61st Annual Meeting of ACL (Volume 1: Long Papers))

Subscriber deck — free during early access

1 cards in “2.3 Finetuning the LM to Follow Instructions” · whole deck

2.3 Finetuning the LM to Follow Instructions

  1. How was the model fine-tuned on Self-Instruct data, and why use several templates?
    Instruction and input are concatenated as the prompt and the model is trained to generate the output. Multiple templates (with or without “Task:”, “Input:”, “Output:” prefixes, varying line breaks) make it robust to different formats.
    • Wang et al., 2023, Self-Instruct (Proceedings of the 61st Annual Meeting of ACL (Volume 1: Long Papers)), §2.3, p. 13487

Source

  • Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi and Hannaneh Hajishirzi. 2023. Self-Instruct: Aligning Language Models with Self-Generated Instructions. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 13484–13508. License: CC BY 4.0. Flashcards adapted from this work. doi:10.18653/v1/2023.acl-long.754 https://aclanthology.org/2023.acl-long.754/