huggingface / huggingface/setfit
From which number of training samples does it not make sense anymore to use SetFit?
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Description
I'm building a classifier that assigns news articles to one of 8 categories, I was wondering if there was a rule of thumb that over a certain number of training samples per class it would make more sense to use a traditional transformer classifier such as roberta-large? Or will SetFit always be more accurate?
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