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3 votes

What is the difference between fine tuning and variants of few shot learning?

I believe the standard meanings are as follows, but not everyone uses words in the same way, so you might see examples that differ. Fine tuning refers to slightly changing the weights of a pre-trained ...
Lee Reeves's user avatar
1 vote

Using a pre-trained model to generate labels to data to then train a model on

If using BART is already giving you good results, why do you need a new model? Not a rhetorical question. You might have good reasons for that. Training a model with less parameters optimized only on ...
Edoardo Guerriero's user avatar
1 vote

Zero shot learning available labels in testing set

The formal definition of zero-shot learning is that given labeled training instances $D_{tr}$ belonging to the seen classes $S$, the aim is to learn a classifier $f^u(·):X→U$ that can classify testing ...
ddaedalus's user avatar
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