TuneAhead: Predicting Fine-tuning Performance Before Full Training Begins

Yuxiang Luo, Haonan Long, Chen Wang +6

Fine-tuning large language models (LLMs) is compute-intensive and error-prone: model performance depends sensitively on data quality and hyperparameter choices, and naïve runs can…