Romanian Question Answering Using Transformer Based Neural Networks

"Question answering is the task of predicting answers for questions based on a context paragraph. It has become especially important, as large amounts textual data available online requires not only gathering information but also findings specific to questions. In this work, we present experiments evaluated XQuAD-ro question dataset that been recently published translation SQuAD into Romanian. Our bestperforming model, Romanian fine-tuned BERT, achieves an F1 score 0.80 and EM 0.73. We show fine-tuning model with addition slightly increases evaluation metrics. Keywords phrases: answering, deep learning, Transformer, "