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END-TO-END MODEL TRAINING METHOD AND APPARATUS, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM

机译:端到端模型训练方法和装置,以及非暂时性计算机可读介质

摘要

The present disclosure provides an end-to-end model training method and apparatus, which relates to a field of artificial intelligence technologies. The method includes: obtaining training data containing a plurality of training samples, in which the plurality of training samples include an original sequence, a target sequence and a corresponding tag list, the tag list includes importance tags in the target sequence and avoidance tags corresponding to the importance tags, and the avoidance tags are irrelevant tags corresponding to the importance tags; and adopting the training data to train a preset end-to-end model until a value of a preset optimization target function is smaller than a preset threshold.
机译:本公开提供了一种端到端模型训练方法和装置,其涉及人工智能技术领域。该方法包括:获得包含多个训练样本的训练数据,其中多个训练样本包括原始序列,目标序列和相应的标签列表,标签列表包括目标序列中的重要性标签,并避免对应的标签重要性标签和避免标签是与重要标签对应的无关标签;并采用培训数据训练预设的端到端模型,直到预设优化目标函数的值小于预设阈值。

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