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Register a new userPapago's Submission for the WMT21 Quality Estimation Shared Task
إرسال باباجو لتقدير جودة WMT21 المهمة المشتركة
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تصف هذه الورقة تقديم Papago إلى مهمة تقدير الجودة WMT 2021 1: التقييم المباشر على مستوى الجملة.يستكشف نظام تقدير الجودة متعدد اللغات لدينا مزيج من نماذج اللغة المحددة مسبقا وبنية التعلم متعددة المهام.نقترح خط أنابيب تدريب تكراري يعتمد على ما يحقظ بكميات كبيرة من البيانات الاصطناعية داخل المجال وتصفية البيانات الذهبية (المسمى).ثم قمنا بضغط نظامنا عبر تقطير المعرفة من أجل تقليل المعلمات بعد الحفاظ على أداء قوي.تنفذ أنظمتنا متعددة اللغات متعددة اللغات بشكل تنافسي في تعدد اللغات وجميع إعدادات زوج اللغة الفردية 11 بما في ذلك صفر النار.
This paper describes Papago submission to the WMT 2021 Quality Estimation Task 1: Sentence-level Direct Assessment. Our multilingual Quality Estimation system explores the combination of Pretrained Language Models and Multi-task Learning architectures. We propose an iterative training pipeline based on pretraining with large amounts of in-domain synthetic data and finetuning with gold (labeled) data. We then compress our system via knowledge distillation in order to reduce parameters yet maintain strong performance. Our submitted multilingual systems perform competitively in multilingual and all 11 individual language pair settings including zero-shot.
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