![]() As a result, the pre-trained BERT model can be fine-tuned with just one additional output layer to create state-of-the-art models for a wide range of tasks, such as question answering and language inference, without substantial task-specific architecture modifications.īERT is conceptually simple and empirically powerful. 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. ![]() Download a PDF of the paper titled BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, by Jacob Devlin and 3 other authors Download PDF Abstract:We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.
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