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Is multi-token iPET be able to trained on a multi-class classification dataset?
Hi, I want to adapt muti-token iPET to a multi-classification task. However, all examples in the paper are binary classification. I am wondering can iPET be trained for multi-classification tasks?
I remember Timo Schick mentioning that this is not possible yet somewhere in this repository a while ago.
I used plain Bert to train my multi classification task
@GryffindorLi @chris-aeviator I think it is possible to support multiple categories. Initially, I understand that PET can be used on multiple tokens, so it should be able to be adapted to multi-category tasks. Besides PET, I can think of two ways to use it, but I'm not sure which one will work better
- classify multi-categories by number 1-N (N>10) and then predict the number to classify? This will lose semantic information
- splice the multiclassification labels after the text as a generation task and let the model do the generation of the labels?