In my dataset, there are a total of 9 classes and their distribution is,
223,119,42,37,24,23,16,12,4.
Instead of giving all classes to my model, I am giving the last four classes and trying a few-shot classification(my assumption is to try few-shot we have to pretrained model because the model already had some knowledge so that it can able to learn from a few samples). that is the reason I am an HF model
Correct me if my assumption is wrong and give any suggestion to try a few-shot with HF, That will be greatly helpful.
Here I am not splitting the data into train and validation because my samples are fewer. I am evaluating my model by manually giving unlabelled samples to the model.
I am using TFdistilbert for the sequence classification model.