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Register a new userEstBERT: A Pretrained Language-Specific BERT for Estonian
إستبيرت: بيرت محددة باللغة المحددة للإستونية
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تقدم هذه الورقة Estbert، وهو طراز بيرت محول محول محول محول كبير مسبقا للإستونية.قامت العمل الحديثة بتقييم نماذج بيرت متعددة اللغات على المهام الإستونية ووجدتها أن تتفوق على الأساس.ومع ذلك، بناء على الدراسات القائمة على اللغات الأخرى، من المتوقع أن تتحسن نموذج بيرت خاص باللغة من المتوقعين على تلك المتعددة اللغات.نحن نصف أول عملية محاكمة Estbert ثم تقديم نتائج النماذج المستندة إلى Estbert Finetuned لمهام NLP متعددة، بما في ذلك نقاط البيع والعلامات المورفولوجية، وتحليل التبعية، والتعرف على الكيان المسمى وتصنيف النص.تظهر نتائج التقييم أن النماذج القائمة على Estbert تفوقت نماذج بيرت متعددة اللغات متعددة اللغات على خمس مهام من أصل سبعة، وتوفير المزيد من الأدلة تجاه الرأي أن نماذج Berty-الخاصة باللغة التدريبية لا تزال مفيدة، حتى عندما تتوفر نماذج متعددة اللغات.
This paper presents EstBERT, a large pretrained transformer-based language-specific BERT model for Estonian. Recent work has evaluated multilingual BERT models on Estonian tasks and found them to outperform the baselines. Still, based on existing studies on other languages, a language-specific BERT model is expected to improve over the multilingual ones. We first describe the EstBERT pretraining process and then present the models' results based on the finetuned EstBERT for multiple NLP tasks, including POS and morphological tagging, dependency parsing, named entity recognition and text classification. The evaluation results show that the models based on EstBERT outperform multilingual BERT models on five tasks out of seven, providing further evidence towards a view that training language-specific BERT models are still useful, even when multilingual models are available.
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