Category: text-classification
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Choose the Right One: Evaluating Topic Models for Business Intelligence
Choose the Right One: Evaluating Topic Models for Business Intelligence Topic models are used in businesses to classify brand-related text datasets (such as product and site reviews, surveys, and social media comments) and to track how customer satisfaction metrics change over time. There is a myriad of recent topic models one can choose from: the…
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R.E.D.: Scaling Text Classification with Expert Delegation
R.E.D.: Scaling Text Classification with Expert Delegation With the new age of problem-solving augmented by Large Language Models (LLMs), only a handful of problems remain that have subpar solutions. Most classification problems (at a PoC level) can be solved by leveraging LLMs at 70–90% Precision/F1 with just good prompt engineering techniques, as well as adaptive…
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How to Fine-Tune DistilBERT for Emotion Classification
How to Fine-Tune DistilBERT for Emotion Classification The customer support teams were drowning with the overwhelming volume of customer inquiries at every company I’ve worked at. Have you had similar experiences? What if I told you that you could use AI to automatically identify, categorize, and even resolve the most common issues? By fine-tuning a…
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How to Utilize ModernBERT and Synthetic Data for Robust Text Classification
How to Utilize ModernBERT and Synthetic Data for Robust Text Classification Learn how to fine-tune ModernBERT and create augmentations of text samples Continue reading on Towards Data Science » Eivind Kjosbakken Go to original source