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Register a new userAdversities are all you need: Classification of self-reported breast cancer posts on Twitter using Adversarial Fine-tuning
الشدائز هي كل ما تحتاجه: تصنيف مشاركات سرطان الثدي التي تم الإبلاغ عنها على Twitter باستخدام خصصي صقل
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في هذه الورقة، نصف إدخال نظامنا للمهمة المشتركة 8 في SMM4H-2021، وهو في التصنيف التلقائي لمرورات سرطان الثدي التي تم الإبلاغ عنها على Twitter.في نظامنا، نستخدم نهج ضبط طراز بلغة قائمة على المحولات لتحديد التغريدات تلقائيا في فئة التقارير الذاتية.علاوة على ذلك، فإننا نضمن ضبطا غرامة مقيم تدريجيا لتحسين متانة النموذج العام.حقق نظامنا درجة F1 من 0.8625 على مجموعة التطوير و 0.8501 في مجموعة الاختبار في مهمة مشتركة - 8 من SMM4H-2021.
In this paper, we describe our system entry for Shared Task 8 at SMM4H-2021, which is on automatic classification of self-reported breast cancer posts on Twitter. In our system, we use a transformer-based language model fine-tuning approach to automatically identify tweets in the self-reports category. Furthermore, we involve a Gradient-based Adversarial fine-tuning to improve the overall model's robustness. Our system achieved an F1-score of 0.8625 on the Development set and 0.8501 on the Test set in Shared Task-8 of SMM4H-2021.
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