Need clarity on "padding" parameter in Bert Tokenizer
Hi All,I have been fine tuning aBERTmodel for sentence classification. In training, while tokenization I had passed these parameterspadding="max_length", truncation=True, max_length=150but while inferencing it is still predicting even ifpadding="max_length"parameter is not being passed.Surprisingly, predictions are same in both the cases whenpadding="max_length"is passed or not but ifpadding="max_length"is not being passed, inferencing is much faster.So, I need some clarity on the parameter “padding” in Bert Tokenizer. Can someone help me to understand how bert is able to predict even without the padding since the length of the sentences will differ and does it have any negative consequences Ifpadding="max_length"is not passed while inferencing? Any help would be highly appreciated.Thanks