BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers. As a result, the pre-trained BERT model can be fine-tuned with
Challenges of reproducing R-NET neural network using Keras · YerevaNN
Challenges of reproducing R-NET neural network using Keras 25 Aug 2017 By Martin Mirakyan, Karen Hambardzumyan and Hrant Khachatrian. In this post we describe our attempt to re-implement a neural architecture for automated question answering called R-NET, which is developed by the Natural Language Computing Group of Microsoft Research Asia. This architecture demonstrates the best performance among
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