Let's say we want to fine-tune the model (any of the taxonomies - ekman/original) on another dataset having a different number of classes for e.g. only positive and negative. Then what's the correct procedure to do it?
Currently, If I prepare the data in the same format (.tsv files with data and labels), and put the labels.txt as having only two classes, the training seems to run. But is this way correct? Or any other changes need to be made inside the model training?
Let's say we want to fine-tune the model (any of the taxonomies - ekman/original) on another dataset having a different number of classes for e.g. only positive and negative. Then what's the correct procedure to do it?
Currently, If I prepare the data in the same format (.tsv files with data and labels), and put the
labels.txtas having only two classes, the training seems to run. But is this way correct? Or any other changes need to be made inside the model training?