This article, written by Courtlin Holt-Nguyen and published on Towards AI, discusses the BERT Transformer model in the context of machine learning and natural language processing (NLP). The transformer model was introduced as a way to improve the performance of translation systems, and it incorporates the concept of ‘attention’ to transform one sequence of input text into another sequence of output text. The article explores how BERT can be fine-tuned for state-of-the-art sentiment analysis using Hugging Face.

source update: Fine-tune BERT for State-of-the-art sentiment… – Towards AI

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