text: Title: selene_sdk issue
  Body: 
  
  
  i got this error message and couldn't find where's the issue 
  ```
  ValueError                                Traceback (most recent call last)
  <ipython-input-3-c4059c3098d2> in <module>
  ----> 1 parse_configs_and_run(configs, lr=0.01)
        2 print("Fin de Exécussion")
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/selene_sdk/utils/config_utils.py in parse_configs_and_run(configs, create_subdirectory, lr)
      349               "Using a random seed ensures results are reproducible.")
      350 
  --> 351     execute(operations, configs, current_run_output_dir)
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/selene_sdk/utils/config_utils.py in execute(operations, configs, output_dir)
      190                     "evaluate" in operations:
      191                 train_model.create_test_set()
  --> 192             train_model.train_and_validate()
      193 
      194         elif op == "evaluate":
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/selene_sdk/train_model.py in train_and_validate(self)
      428         for step in range(self._start_step, self.max_steps):
      429             self.step = step
  --> 430             self.train()
      431 
      432             if step % self.nth_step_save_checkpoint == 0:
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/selene_sdk/train_model.py in train(self)
      461 
      462         predictions = self.model(inputs.transpose(1, 2))
  --> 463         loss = self.criterion(predictions, targets)
      464 
      465         self.optimizer.zero_grad()
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
     1100         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
     1101                 or _global_forward_hooks or _global_forward_pre_hooks):
  -> 1102             return forward_call(*input, **kwargs)
     1103         # Do not call functions when jit is used
     1104         full_backward_hooks, non_full_backward_hooks = [], []
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/torch/nn/modules/loss.py in forward(self, input, target)
      601 
      602     def forward(self, input: Tensor, target: Tensor) -> Tensor:
  --> 603         return F.binary_cross_entropy(input, target, weight=self.weight, reduction=self.reduction)
      604 
      605 
  
  ~/anaconda3/envs/selene-gpu/lib/python3.6/site-packages/torch/nn/functional.py in binary_cross_entropy(input, target, weight, size_average, reduce, reduction)
     2906         raise ValueError(
     2907             "Using a target size ({}) that is different to the input size ({}) is deprecated. "
  -> 2908             "Please ensure they have the same size.".format(target.size(), input.size())
     2909         )
     2910 
  
  ValueError: Using a target size (torch.Size([64, 12])) that is different to the input size (torch.Size([64, 11])) is deprecated. Please ensure they have the same size.
  ```
  