Hi guys,
I’d like to understand if there was any architectural difference between a Question-Answering model trained with the SQuAD1.0 dataset and SQuAD2.0 dataset. From what I understand the model trained with SQuAD2.0 should be capable of understanding if no answer can be provided given a certain question-context pair. Does it do so by giving a lower score to the most-likely answer in the context?
Moreover, how’s the score of an answer exactly calculated ( I’m referring to the score provided by the question-answering pipeline)?