How to Prevent Overfitting When Fine-Tuning AI Models
fine. This guide covers how to detect overfitting early and prevent it — with LoRA, data curation, epoch limits, and targeted regularization techniques backed by recent research
LLM training
How to Prepare a Dataset for Fine-Tuning a Language Model
Most fine-tuning failures happen before training starts. Bad labels, missing EOS tokens, contaminated test sets — these are data bugs that show up as model bugs. This guide covers every stage of dataset preparation: format selection, cleaning, deduplication, labeling quality, splitting, and tokenization. With the research behind every claim.