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  • 标题:SarcasmDet at Sarcasm Detection Task 2021 inArabic usingAraBERTPretrained Model
  • 本地全文:下载
  • 作者:Dalya Faraj ; Dalya Faraj ; Malak Abdullah
  • 期刊名称:Conference on European Chapter of the Association for Computational Linguistics (EACL)
  • 出版年度:2021
  • 卷号:2021
  • 页码:345-350
  • 语种:English
  • 出版社:ACL Anthology
  • 摘要:This paper presents one of the top five winning solutions for the Shared Task on Sarcasm and Sentiment Detection in Arabic (Subtask-1 Sarcasm Detection). The goal of the task is to identify whether a tweet is sarcastic or not. Our solution has been developed using ensemble technique with AraBERT pre-trained model. We describe the architecture of the submitted solution in the shared task. We also provide the experiments and the hyperparameter tuning that lead to this result. Besides, we discuss and analyze the results by comparing all the models that we trained or tested to achieve a better score in a table design. Our model is ranked fifth out of 27 teams with an F1 score of 0.5985. It is worth mentioning that our model achieved the highest accuracy score of 0.7830.
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