Currently, NMT models are usually trained with the word-level loss (i.e., cross-entropy) under the teacher forcing algorithm (Williams and Zipser, *Corresponding Author 1989), which forces the model to generate translation strictly matching the ground-truth at the word level.
in practice it is impossible to generate translation totally the same as ground truth.