This is the third post in this series about distilling BERT with multimetric Bayesian optimization. Part 1 discusses the background for the experiment and Part 2 discusses the setup for the Bayesian optimization. In my previous posts, I discussed the importance of BERT for transfer learning in NLP, and established the foundations of this experiment’s design. In this post, I discuss the model…
]]>This is the second post in this series about distilling BERT with multimetric Bayesian optimization. Part 1 discusses the background for the experiment and Part 3 discusses the results. In my previous post, I discussed the importance of the BERT architecture in making transfer learning accessible in NLP. BERT allows a variety of problems to share off-the-shelf, pretrained models and moves NLP…
]]>This is the first post in a series about distilling BERT with multimetric Bayesian optimization. Part 2 discusses the set up for the Bayesian experiment, and Part 3 discusses the results. You’ve all heard of BERT: Ernie’s partner in crime. Just kidding! I mean the natural language processing (NLP) architecture developed by Google in 2018. That’s much less exciting, I know. However…
]]>Natural language systems have become the go-between for humans and AI-assisted digital services. Digital assistants, chatbots, and automated HR systems all rely on understanding language, working in the space of question answering. So what are question answering (QA) systems and why do they matter? In general, QA systems take some sort of context in the form of natural language and retrieve…
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