免费网站建设信息,北京网站推广排名,网站模板使用教程,爱站工具包手机版ArXiv#xff1a;https://arxiv.org/abs/1910.01108 Train Loss: DistilBERT#xff1a; DistilBERT具有与BERT相同的一般结构#xff0c;层数减少2倍#xff0c;移除token类型嵌入和pooler。从老师那里取一层来初始化学生。 The token-type embeddings and the pooler a…ArXivhttps://arxiv.org/abs/1910.01108 Train Loss: DistilBERT DistilBERT具有与BERT相同的一般结构层数减少2倍移除token类型嵌入和pooler。从老师那里取一层来初始化学生。 The token-type embeddings and the pooler are removed while the number of layers is reduced by a factor of 2. Most of the operations used in the Transformer architecture (linear layer and layer normalisation) are highly optimized in modern linear algebra frameworks。 we initialize the student from the teacher by taking one layer out of two. 大batch,4k,动态mask,去掉NSP 训练数据和BERT一样