After epoch 1 it is throwing this error
Model: resnet50 Frozen Layers: False
Epoch 1/50
train Loss: 0.2108 Acc: 0.9226 TPR: 0.9270 FPR: 0.0819
IndexError                                Traceback (most recent call last)
 in 
17         optimizer = optim.Adam(parameters)
18
—> 19         net = train_model(net, criterion, optimizer, num_epochs=num_epochs, name=name)
20
21         net = net.to(torch.device(‘cpu’))
 in train_model(model, criterion, optimizer, num_epochs, dataset_sizes, name)
41
42                     # criterion is the loss
—> 43                     loss = criterion(outputs, labels)
44
45                     # then back propogate the loss
~/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
530             result = self._slow_forward(*input, **kwargs)
531         else:
–> 532             result = self.forward(*input, **kwargs)
533         for hook in self._forward_hooks.values():
534             hook_result = hook(self, input, result)
~/anaconda3/lib/python3.7/site-packages/torch/nn/modules/loss.py in forward(self, input, target)
914     def forward(self, input, target):
915         return F.cross_entropy(input, target, weight=self.weight,
–> 916                                ignore_index=self.ignore_index, reduction=self.reduction)
917
918
~/anaconda3/lib/python3.7/site-packages/torch/nn/functional.py in cross_entropy(input, target, weight, size_average, ignore_index, reduce, reduction)
2019     if size_average is not None or reduce is not None:
2020         reduction = _Reduction.legacy_get_string(size_average, reduce)
-> 2021     return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
2022
2023
~/anaconda3/lib/python3.7/site-packages/torch/nn/functional.py in nll_loss(input, target, weight, size_average, ignore_index, reduce, reduction)
1836                          .format(input.size(0), target.size(0)))
1837     if dim == 2:
-> 1838         ret = torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
1839     elif dim == 4:
1840         ret = torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
IndexError: Target 2 is out of bounds.