HunSum-1 an abstractive summarization dataset for Hungarian /
We introduce HunSum-1 : a dataset for Hungarian abstractive summarization, consisting of 1.14M news articles. The dataset is built by collecting, cleaning and deduplicating data from 9 major Hungarian news sites through CommonCrawl. Using this dataset, we build abstractive summarizer models based on...
Elmentve itt :
Szerzők: | |
---|---|
Testületi szerző: | |
Dokumentumtípus: | Könyv része |
Megjelent: |
2023
|
Sorozat: | Magyar Számítógépes Nyelvészeti Konferencia
19 |
Kulcsszavak: | Nyelvészet - számítógép alkalmazása |
Tárgyszavak: | |
Online Access: | http://acta.bibl.u-szeged.hu/78416 |
Tartalmi kivonat: | We introduce HunSum-1 : a dataset for Hungarian abstractive summarization, consisting of 1.14M news articles. The dataset is built by collecting, cleaning and deduplicating data from 9 major Hungarian news sites through CommonCrawl. Using this dataset, we build abstractive summarizer models based on huBERT and mT5. We demonstrate the value of the created dataset by performing a quantitative and qualitative analysis on the models’ results. The HunSum-1 dataset, all models used in our experiments and our code1 are available open source. |
---|---|
Terjedelem/Fizikai jellemzők: | 231-243 |
ISBN: | 978-963-306-912-7 |