T5 model for classification doesn't work properly for large number of classes.
T5 model works properly for 50 class classification but when we try for 100 classes it outputs empty string ("") for a large number of test data. Is this model suitable for multi-class classification with a large number of classes? If yes, what do you think might be the problem with what I am doing. 
Hi, @HiteshVamshi , what you are trying is highly experimental, I haven't seen anyone using T5 for 100 class classification. So you'll probably need to experiment with it.

I would like to know few more details
1) What is the size of your dataset
2) which version of t5 are you using (t5-small, t5-base, t5-large etc)
3) how many epochs  <|||||>Hi, @patil-suraj , I was also experimenting with the T5 model. I got a good performance for 50 classes so tried with more.
-The size of the dataset used was 65k.
-I used T5-small.
-I tested for 10 epochs. But there was no significant improvement after 3 epochs.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
<|||||>Can we use the T5 model with only 2000 samples for classifications (not a lot of classes, just around 10)? what about binary classification?