Hello,
I have a multi classification model ( with 5 classes). The model looks like this:
classifier(
  (embedding): Embedding(28564, 100)
  (lstm): LSTM(100, 32, num_layers=2, batch_first=True, dropout=0.2, bidirectional=True)
  (fc): Linear(in_features=64, out_features=5, bias=True)
  (act): Sigmoid()
)

But when I do predict to a new  sampel, I have an output like this:
tensor([[ 4.9442, -4.3852,  0.8900, -2.8472, -4.5958]], device='cuda:0',
       grad_fn=<SliceBackward>)

What should I modify to have an output as a label (0,1,2,3,4)?
Thanks in advance.