Fine-tuned BERT on AG News dataset to classify headlines into 4 categories achieving 87.40% accuracy.
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Updated
Apr 18, 2026 - Python
Fine-tuned BERT on AG News dataset to classify headlines into 4 categories achieving 87.40% accuracy.
End-to-end MLOps pipeline for news classification — experiment tracking with MLflow, data versioning with DVC, FastAPI serving, drift monitoring with Evidently AI, and a 4-job GitHub Actions CI/CD that builds and pushes to DockerHub on every commit.
End-to-end NLP text classification pipeline on AG News, a custom LLaMA-inspired transformer with RoPE/RMSNorm/SwiGLU, Optuna + MLflow hyperparameter tuning, uncertainty-aware evaluation, bundle promotion, FastAPI serving, and Streamlit dashboard. Deployable via Docker & HF Spaces.
Fine-tuned GPT-2 on AG News for news classification, with reproducible preprocessing, training, evaluation, and FP32 vs INT8 / 4-bit inference comparison.
Parameter-efficient fine-tuning of DistilBERT using LoRA for sentiment and topic classification, with CLI, API, and interactive chatbot interfaces.
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