Update README.md

README.md

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 News Abstractive Summarization for Spanish (NASES) is a Transformer encoder-decoder model, with the same hyper-parameters than BART, to perform summarization of Spanish news articles. It is pre-trained on a combination of several self-supervised tasks that help to increase the abstractivity of the generated summaries. Four pre-training tasks have been combined: sentence permutation, text infilling, Gap Sentence Generation, and Next Segment Generation. Spanish newspapers, and Wikipedia articles in Spanish were used for pre-training the model (21GB of raw text -8.5 millions of documents-).
 
-NASES is finetuned for the summarization task on 1.802.919 documents from the Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (DACSA).
+NASES is finetuned for the summarization task on 1.802.919 (document, summary) pairs from the Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (DACSA).