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论文中数据增强在小样本数据集上取得了大幅的性能提升,但是数据增强具体的方案没有细谈。我根据论文中的描述,不知道按照以下理解是否正确:
论文中的数据增强是指,通过添加 训练数据集外 相似的文本数据,让教师网络和学生网络在这些样本中通过 中间层 hidden or att 的匹配 loss 进行学习,而忽略掉 logits,因此数据增强这部分其实不需要任何标签。
感谢 HFL 能一直提供如此之多的高质量开源项目,实实在在的为中文 NLP 带来了巨大的积极影响!
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