Hugging Face Articles

Fine-tuning pre-trained Transformer models is one of the most effective ways to achieve high performance on NLP tasks with minimal training data. In this guide, we walk through practical examples using Hugging Face Transformers, including fine-tuning DistilBERT for sentiment analysis, BERT for token classification (Named Entity Recognition), and BERT for question answering. You'll learn how to load checkpoints, prepare datasets, configure training, and evaluate model performance step by step.