Almog_gueta Knowledge Is a Region in Weight Space for Fine Tuned Language Model 2023
[TOC] Title: Knowledge Is a Region in Weight Space for Fine Tuned Language Model Author: Almog Gueta et. al. Publish Year: 12 Feb 2023 Review Date: Wed, Mar 1, 2023 url: https://arxiv.org/pdf/2302.04863.pdf Summary of paper Motivation relatively little is known a bout the relationships between different models, especially those trained or tested on different datasets. Contribution we demonstrate that fine-tuned models that were optimized for high performance, reside in well-defined regions in weight space, and vice versa language models that have been fine-tuned on the same dataset form a tight cluster in the same weight space and that models fine-tuned on different datasets from the same underlying task form a looser cluster. traversing around the region between the models reaches new models that perform comparably or even better than models found via fine-tuning Our findings demonstrate that a model positioned between two similar models can acquire the knowledge of both. We leverage this finding and design a method to pick a better model for efficient fine-tuning. more findings ...