[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un

Bert 预训练思路
[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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Bert 预训练模型 Bert 预训练两大子任务

  • Mask Token Prediction: 对于Mask的位置,多分类任务,从此表中预测处正确的词
  • Next Sentence Prediction: 输入两个句子,判断S1和S2是否是上下句的关系。
[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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Mask Token Prediction [论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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Next Sentence Prediction StructBert
[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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对于单个句子,考虑Word-Leval Prediction
(1) 预测被Mask的词
(2) 选择一些不包含Mask词的连续三元组,打乱三元组的顺序,预测重建该三元组
[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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最后在句子被预测处理过的位置所对应的正确单词。
对于两个句子,考虑Sentence-Level Prediction
[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un
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【[论文阅读笔记 --- 13] StructBERT: Incorporating Language Structures into Pre-training for Deep Language Un】(1) 考虑为三分类任务,给定句子对S1和S2,存在以下三种情况,S2是S1的下一句,S2是S1的上一句,S1和S2没有上下句关系。

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