Ncu-iisr: Pre-trained language model for cantemist named entity recognition

Jen Chieh Han, Richard Tzong Han Tsai

研究成果: 雜誌貢獻會議論文同行評審

2 引文 斯高帕斯(Scopus)


Since BERT has brought a huge improvement in various NLP tasks, the great constructed pre-trained language model shows its power of being fine-tuned in other downstream tasks either. In this paper, NCU-IISR team adopted the Spanish BERT, BETO, as our pre-trained model, and the model was finetuned on CANTEMIST Named Entity Recognition (NER) data. Besides, we also compared it with another fine-tuned version, which was trained on an external Spanish medical text. Finally, our best score achieved an F1-measure of 0.85 in the official test set result for CANTEMIST-NER task.

頁(從 - 到)347-351
期刊CEUR Workshop Proceedings
出版狀態已出版 - 2020
事件2020 Iberian Languages Evaluation Forum, IberLEF 2020 - Malaga, Spain
持續時間: 23 9月 2020 → …


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