I am trying to do multiclass classification for the sentence pair task. I uploaded my custom dataset of train and test separately in the hugging face data set and trained my model and tested it and was trying to see the f1 score and accuracy.
Okay I realized what was wrong.
So MRPC itself is a binary classification task, so your dataset has to have binary target. You’re loading MRPC as metric yet it says your original dataset is multiclass. Is it like that?
Apparently you can’t change the average argument for a good reason.
@merve Do you have any idea which metric should I use for multiclass classification if I want to have all the results of precision, recall, f1, and accuracy.
Hello! Trying to use recall for a BERT fine-tuning notebook. I just want to understand why is it that after .compute(pred, references, average) we query for [“precision”]. If it’s recall should I input [“recall”] after the .compute() method?
EDIT: my script for multiclass BERT fine tuning was able to run successfully with the following: