Train calls the loss function as loss(d...) if each datum d is a tuple, i.e., with your definition of data it is called as loss( (V_train, S_train)... ) = loss(V_train, S_train). On the other hand, your loss function is defined as taking input and target as arguments (in that order). Thus, your model learns to map V to S instead of the intended mapping. Flipping either the order of targets and inputs in your data set or in the arguments of the loss function will fix it.
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