ItaliaNLP @ TAG-IT: TAG-IT 2020作者分析编号(短论文)

Daniela Occhipinti, A. Tesei, Maria Iacono, C. Aliprandi, Lorenzo De Mattei
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引用次数: 1

摘要

在本文中,我们描述了我们用于参与EVALITA 2020任务TAG-it的系统。我们开发的第一个系统使用线性支持向量机作为学习算法。另外两个系统基于预训练的意大利语模型UmBERTo:其中一个是按照多任务学习方法开发的,而另一个是按照单任务学习方法开发的。这些系统已经在TAG-it官方测试集上进行了评估,并在所有TAG-it子任务中排名第一,证明了我们所遵循的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ItaliaNLP @ TAG-IT: UmBERTo for Author Profiling at TAG-it 2020 (short paper)
In this paper we describe the systems we used to participate in the task TAG-it of EVALITA 2020. The first system we developed uses linear Support Vector Machine as learning algorithm. The other two systems are based on the pretrained Italian Language Model UmBERTo: one of them has been developed following the Multi-Task Learning approach, while the other following the Single-Task Learning approach. These systems have been evaluated on TAG-it official test sets and ranked first in all the TAG-it subtasks, demonstrating the validity of the approaches we followed.
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