RuntimeError: size mismatch, m1: [64 x 8192], m2: [2048 x 76

---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-38-32e1a80e12b8> in <module>()
     16         optimiser.zero_grad()
     17
---> 18         logps = model(images)
     19         loss = criterion(logps, labels)
     20

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    487                 if isinstance(var, dict):
    488                     var = next((v for v in var.values() if isinstance(v, torch.Tensor)))
--> 489                 else:
    490                     var = var[0]
    491             grad_fn = var.grad_fn

/usr/local/lib/python3.6/dist-packages/torchvision/models/resnet.py in forward(self, x)
    149         x = self.avgpool(x)
    150         x = x.view(x.size(0), -1)
--> 151         x = self.fc(x)
    152
    153         return x

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    487                 if isinstance(var, dict):
    488                     var = next((v for v in var.values() if isinstance(v, torch.Tensor)))
--> 489                 else:
    490                     var = var[0]
    491             grad_fn = var.grad_fn

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/container.py in forward(self, input)
     90         for module in self._modules.values():
     91             input = module(input)
---> 92         return input
     93
     94

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    487                 if isinstance(var, dict):
    488                     var = next((v for v in var.values() if isinstance(v, torch.Tensor)))
--> 489                 else:
    490                     var = var[0]
    491             grad_fn = var.grad_fn

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/linear.py in forward(self, input)
     65     :math:`y = x_1 A x_2 + b`
     66
---> 67     Args:
     68         in1_features: size of each first input sample
     69         in2_features: size of each second input sample

/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in linear(input, weight, bias)
   1350
   1351 # loss
-> 1352
   1353
   1354 def nll_loss(input, target, weight=None, size_average=None, ignore_index=-100,

RuntimeError: size mismatch, m1: [64 x 8192], m2: [2048 x 768] at /pytorch/aten/src/THC/generic/THCTensorMathBlas.cu:266