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 as **predicted start_index** and **predicted end_index**.
But, sometimes **predicted start_index** would less than **predicted 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 = 4`
`predicted end_index = 2`

It is not reasonable.
Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.
Could you ask your question on the [forum](https://discuss.huggingface.co) instead?

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