At the beginning of training, the model is not well-trained and thus selecting more often the true previous token should be helpful; whereas at the end of training the sampling strategy should favor sampling from the model more often, as this corresponds to the true inference situation.
the probability of using y t−1 will be initially high and then decrease during training.