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I am looking to solve a multi-class classification problem with long sequences of text with some rows having 1000's of tokens. Some of the state of the art methods such as BERT have a token limit and I was wondering what is currently being done to handle longer text sequences when dealing with classification?

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Traditional methods don't have such a limit: Naive Bayes, SVM, decision trees...

Also see https://stackoverflow.com/questions/58636587/how-to-use-bert-for-long-text-classification

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