Fine tunning QA model in SQUAD 2 dataset with more than one answer
Hello.I had been able to fine tune successfully some models for QA in custom SQUAD dataset using scripts likerun_qa.pyandrun_seq2sqe_qa.pyfromhttps://github.com/huggingface/transformers/blob/main/examples/pytorch/question-answering/But this scripts are made only for SQUAD datasets in which for every question, only one possible answer is available, because in the code you get this:Forrun_qa.py:start_char = answers[“answer_start”][0]Forrun_seq2seq_qa.py:targets = [answer[“text”][0] if len(answer[“text”]) > 0 else “” for answer in answers]In my SQUAD dataset for some questions I could have several answers. How should I deal with this situation?I have tried to concatenate the answers using some kind of special chars in order to convert several answers into one, as for example: “answer1 ##AND## answer2”. But this not run properly, never returning that kind of concatenated answers.I’ve also tried converting the SQUAD dataset to a single answer, but in that case, for a question in the same context, the dataset contains several different disjoint answers, and I find this approach weird.So how do you go about training with a custom SQUAD 2 dataset with multiple answers for the same question?Thanks in advance!
2024-03-15T15:53:11Z
did you ever figure out the solution for multiple answers?