Fine-tunes DistilBERT for binary sentiment classification using LoRA, where only 0.3% of parameters are updated, producing a ~1 MB adapter that matches full fine-tuning accuracy. Three-way comparison: zero-shot baseline vs LoRA vs full fine-tune. Served via FastAPI with a web interface.