How many samples for setfit? about setfit HOT 3 OPEN

in my experiment(50 classes and each class used 20 to 50 examples), setfit accuracy is 0.857

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Did you compare it to supervised learning with fine-tuning?

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For the number samples to switch between few shots and standard supervised learning and fine-tuning part, It would be subjective SETfit performance is slightly less then supervised learning and fine-tuning part with lot of examples.

I prefer SETfit where there is no/ low number of training data. (16/ 32 samples per class.). If one has a way out to do labelling should go ahead and use standard supervised learning and fine-tuning. Ultimately its a trade-off game.
But SETfit does gives very good start with few samples.

For num_iterations, I try increasing it till the point i get performance gain. (Treat it as hyper-parameter.)

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