In this paper, we share our best performing submission to the Arabic AI Tasks
Evaluation Challenge (ArAIEval) at ArabicNLP 2023. Our focus was on Task 1,
which involves identifying persuasion techniques in excerpts from tweets and
news articles. The persuasion technique in Arabic texts was detected using a
training loop with XLM-RoBERTa, a language-agnostic text representation model.
This approach proved to be potent, leveraging fine-tuning of a multilingual
language model. In our evaluation of the test set, we achieved a micro F1 score
of 0.64 for subtask A of the competition.

本文介绍了我们在 ArabicNLP 2023 的 ArAIEval 挑战中的最佳提交结果，我们主要关注任务 1，该任务涉及从推特和新闻文章的摘录中识别说服技巧，我们使用 XLM-RoBERTa 进行训练，并在阿拉伯语文本中检测到说服技巧。通过微调多语言语言模型，这种方法表现出很强的效果。在测试集评估中，我们在子任务 A 中取得了 0.64 的微观 F1 分数。