15
Apr
2020
/
Ayush Chaurasia, Contributor

Sentence Classification with huggingface BERT and Hyperparameter Optimization with W&B

In this tutorial, we’ll build a near state of the art sentence classifier leveraging the power of recent breakthroughs in the field of Natural Language Processing. We’ll focus on an application of transfer learning to NLP. We'll use this to create high performance models with minimal effort on a range of NLP tasks. Google’s BERT allowed researchers to smash multiple benchmarks with minimal fine tuning for specific tasks. As a result, NLP research reproduction and experimentation has become more accessible.

We'll use WandB's hyperparameter Sweeps later on. Here's a simple notebook to get you started with sweeps.

Check out the full article and livedashboard here -->

Try BERT fine tuning in a colab →

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