I have 5 classes and would like to use binary classification on one of them.
This is my model:
    model = models.resnet50(pretrained=pretrain_status)
    num_ftrs = model.fc.in_features
    model.fc = nn.Sequential(
      nn.Dropout(dropout_rate),
      nn.Linear(num_ftrs, 2))

I then split my dataset into two folders. The one I want to predict (1) and the rest (0,2,3,4).
However, this setup does two predictions and, as I understand it, binary classification is one prediction (True, False).
My question is how do you properly setup a binary classification model in Pytorch?