在机器翻译过程中，通常为提高翻译效果，会在机器翻译模型中引入一个不参与

In the process of machine translation, usually in order to improve the translation effect, a parallel corpus set that does not participate in training is introduced into the machine translation model as a validation set. In this way, during the training process, a "checkpoint" will be saved in the parameters of the machine translation model when the update is performed at certain intervals. In order to improve the effect of machine translation, the performance of the checkpoint on the entire validation set is often evaluated, and the best checkpoint is selected as the final result of training.

In the process of machine translation, in order to improve the translation effect, a parallel corpus set that does not participate in training will be introduced into the machine translation model as the verification set. In this way, in the process of training, update every certain step, and a "checkpoint" will be saved in the parameters of the machine translation model. In order to improve the effect of machine translation, the performance of the checkpoint in the whole verification set is often evaluated, so as to select the best checkpoint as the final result of training.

In the process of machine translation, in order to improve the translation effect, a parallel corpus set that does not participate in training is usually introduced into the machine translation model as a verification set. In this way, during the training process, updating at regular intervals will save a "checkpoint" in the parameters of the machine translation model. In order to improve the effect of machine translation, the performance of the checkpoint on the whole verification set is often evaluated, so as to select the best checkpoint as the final result of training.