This post is presented in two forms–as a blog post here and as a Colab Notebook here. More broadly, I describe the practical application of transfer learning in NLP to create high performance models with minimal effort on a range of NLP tasks. In this tutorial I’ll show you how to use BERT with the huggingface PyTorch library to quickly and efficiently fine-tune a model to get near state of the art performance in sentence classification. See Revision History at the end for details.
Revised on 3/20/20 - Switched to tokenizer.encode_plus and added validation loss. Chris McCormick About Membership Blog Archive Become an NLP expert with videos & code for BERT and beyond → Join NLP Basecamp now! BERT Fine-Tuning Tutorial with PyTorch
