Class distribution discrepancy training/validation. Loss now uninterpretable?
The validation set is used to estimate how well the model is fitting to your solution space.  For instance, if your training loss continues to decrease but your validation loss remains constant or increases, then you should employ early stopping as to avoid overfitting.  This does not require a weighted loss.

If you wanted to compare the training loss to the validation loss, you cannot use the same weights if the distributions differ.  Instead, you can simply compare the average unweighted loss per set.  The weighted loss is for penalization.