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以公开数据集合训练得到模型,接着在新的数据集上进行三元组任务(triplet)抽取,发现Invalid token的比例很大
是否有考虑过在encoder的embedding部分对词(word)进行编码,decoder部分的任务转换为预测词角标的,从而减少了invalid token的比例?
The text was updated successfully, but these errors were encountered:
这里主要是预训练模型不太能接受word的编码,非法的预测实际上可以在decode的时候进行限制的。需要修改一下decode时候的beam search算法。
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以公开数据集合训练得到模型,接着在新的数据集上进行三元组任务(triplet)抽取,发现Invalid token的比例很大
是否有考虑过在encoder的embedding部分对词(word)进行编码,decoder部分的任务转换为预测词角标的,从而减少了invalid token的比例?
The text was updated successfully, but these errors were encountered: