This project fine-tunes a BERT model on the AG News dataset for supervised news topic classification using pretrained contextual embeddings. The trained model is deployed as a live AI application for real-time inference, demonstrating a complete pipeline from fine-tuning to production deployment.
document-classification multi-class-classification contextual-embeddings nlp-transfer-learning bert-fine-tuning deep-learning-nlp huggingface-transformers language-model-fine-tuning bert-news-classification transformer-text-classification news-topic-detection text-classification-nlp attention-based-models ag-news-benchmark semantic-text-modeling bert-nlp-applications transformer-applications nlp-classifier-systems ai-text-understanding production-nlp-systems
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Updated
May 8, 2026 - Jupyter Notebook