Epoch

An epoch is one complete pass through the full fine-tuning dataset during training. Because fine-tuning datasets are typically small, models are often trained for multiple epochs — but too many epochs on a small, homogeneous dataset leads to overfitting. Common fine-tuning practice uses 1–5 epochs with careful monitoring of validation loss; instruction-tuning runs frequently converge in 2–3 epochs and plateau or degrade thereafter without additional data diversity.