Predicted Start_index < Predicted End_index in BertForQuestionAnswering
We want to fine-tuned a QA model, which is based on BertForQuestionAnswering.After training, we can get a span-start/end scores by input_ids/token_type_ids/attention_mask and choose the indices with maximum span-start/end scores aspredicted start_indexandpredicted end_index.But, sometimespredicted start_indexwould less thanpredicted end_index.If any reasonable method to solve this situation, thanks~Ex:span-start scores = [-0.1, -2.1, 0.7, 1.3, 4.1]span-end scores = [-0.7, 3, 5, -0.7, 3.3]=>predicted start_index = 4predicted end_index = 2It is not reasonable.
2021-09-01T12:28:52Z
Those predictions are not considered usually.