RoBERTweet: A BERT Language Model for Romanian Tweets

Iulian-Marius Tuaiatu, Andrei-Marius Avram, Dumitru-Clementin Cercel, Florin-Claudiu Pop
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引用次数: 0

Abstract

Developing natural language processing (NLP) systems for social media analysis remains an important topic in artificial intelligence research. This article introduces RoBERTweet, the first Transformer architecture trained on Romanian tweets. Our RoBERTweet comes in two versions, following the base and large architectures of BERT. The corpus used for pre-training the models represents a novelty for the Romanian NLP community and consists of all tweets collected from 2008 to 2022. Experiments show that RoBERTweet models outperform the previous general-domain Romanian and multilingual language models on three NLP tasks with tweet inputs: emotion detection, sexist language identification, and named entity recognition. We make our models and the newly created corpus of Romanian tweets freely available.
罗马尼亚语推文的BERT语言模型
开发用于社交媒体分析的自然语言处理(NLP)系统仍然是人工智能研究的一个重要课题。本文介绍了RoBERTweet,这是第一个在罗马尼亚tweets上训练的Transformer架构。我们的RoBERTweet有两个版本,遵循BERT的基础架构和大型架构。用于预训练模型的语料库代表了罗马尼亚NLP社区的新事物,由2008年至2022年收集的所有推文组成。实验表明,RoBERTweet模型在tweet输入的三个NLP任务上优于以前的通用领域罗马尼亚语和多语言模型:情感检测、性别歧视语言识别和命名实体识别。我们免费提供我们的模型和新创建的罗马尼亚语推文语料库。
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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