Writing an LLM from scratch, part 23 -- fine-tuning for classification

Sebastian Raschka's guide demonstrates converting a pretrained language model into a spam classifier by removing its vocabulary prediction head and replacing it with a simpler classification layer. Training only this new head plus the final layer-norm achieved decent results in 15 seconds, but enabling gradients across all layers significantly improved accuracy to nearly perfect spam detection.