Using this approach, your DataLoader will yield numpy array, which you would have to transform into torch.tensors first.
This might be a better approach:
X_train = torch.from_numpy(np.random.randn(64, 2)).float()
y_train = torch.from_numpy(np.random.randint(0, 10, (64,)))
dataset = torch.utils.data.TensorDataset(X_train, y_train)

Also, Variables are deprecated since PyTorch 0.4.0.
If you are using a newer version, you can just remove Variables. The volatile flag was replaced with a with statement:
with torch.no_grad():
    # your validation procedure