HunSum-1 an abstractive summarization dataset for Hungarian - Barta Botond (Magyar Számítógépes Nyelvészeti Konferencia, 2023)
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.