论文标题
深度学习巴西-NLP在Semeval-2020任务9：代码混合推文的情感分析概述
Deep Learning Brasil -- NLP at SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets
论文作者
论文摘要
在本文中，我们描述了一种预测代码混合推文（印度英语）中情感的方法。我们的团队称为codalab中的verissimo.manoel，开发了一种基于四个模型（Multifit，Bert，Albert和XLNet）的合奏的方法。最终的分类算法是这四个模型中所有软max值的一些预测的集合。在Semeval 2020挑战（任务9）的背景下，使用和评估了该体系结构，我们的系统在F1分数上获得了72.7％。
In this paper, we describe a methodology to predict sentiment in code-mixed tweets (hindi-english). Our team called verissimo.manoel in CodaLab developed an approach based on an ensemble of four models (MultiFiT, BERT, ALBERT, and XLNET). The final classification algorithm was an ensemble of some predictions of all softmax values from these four models. This architecture was used and evaluated in the context of the SemEval 2020 challenge (task 9), and our system got 72.7% on the F1 score.
