چکیده مقاله
Nowadays, one of the main challenges in the world ofbig data is finding important information from a large text Atany moment, large volumes of news from different newsagencies are being broadcasted, so reading all this news willrequire spending a lot of time One of the ways to deal with thisproblem is to summarize the text automatically Textsummarization is one of the most important and challengingtasks in the field of natural language processing Summarizingtext means converting the relevant text into a concise form sothat its size is reduced in terms of the number of words,without changing the overall meaning of the text In recentyears, transformers have been very successful in naturallanguage processing tasks, especially text summarization Inthis research, we have trained two pre trained transformers onPersian news texts, mT5 base and mT5 small, and evaluatedtheir performance in summarizing Persian texts
کلیدواژهها
نویسندگان
Vahid Nejad Mahmoodabadi
Computer Engineering Department Faculty of EngineeringShahid Bahonar University of KermanKerman, Iran
Fahimeh Ghasemian
Computer Engineering Department Faculty of EngineeringShahid Bahonar University of KermanKerman, Iran
شیوه ارجاع
Nejad Mahmoodabadi, Vahid and Ghasemian, Fahimeh,1401,Persian Text Summarization via Fine Tuning mT5Transformer,1st International Conference and 6th National Conference on Computers, information technology and applications of artificial intelligence
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی و ششمین کنفرانس ملی کامپیوتر، فناوری اطلاعات و کاربردهای هوش مصنوعی3 اسفند 1401 · اهواز