ALEM at CASE 2021 Task 1: Multilingual Text Classification on News Articles

A. Gürel, Emre Emin
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引用次数: 4

Abstract

We participated CASE shared task in ACL-IJCNLP 2021. This paper is a summary of our experiments and ideas about this shared task. For each subtask we shared our approach, successful and failed methods and our thoughts about them. We submit our results once for every subtask, except for subtask3, in task submission system and present scores based on our validation set formed from given training samples in this paper. Techniques and models we mentioned includes BERT, Multilingual BERT, oversampling, undersampling, data augmentation and their implications with each other. Most of the experiments we came up with were not completed, as time did not permit, but we share them here as we plan to do them as suggested in the future work part of document.
任务1:新闻文章的多语言文本分类
我们参与了ACL-IJCNLP 2021的CASE共享任务。本文总结了我们关于这个共享任务的实验和想法。对于每个子任务,我们分享了我们的方法,成功和失败的方法以及我们对它们的看法。我们在任务提交系统中对除subtask3外的每个子任务提交一次结果,并根据本文给出的训练样本形成的验证集给出分数。我们提到的技术和模型包括BERT、多语言BERT、过采样、欠采样、数据增强及其相互影响。由于时间不允许,我们想到的大多数实验都没有完成,但我们在这里分享它们,因为我们计划按照文档中未来工作部分的建议去做。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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