# Gradient Clipping

> Source: https://sukruyusufkaya.com/en/glossary/gradyan-kirpma
> Updated: 2026-05-13T21:07:54.689Z
> Type: glossary
> Category: matematik-istatistik-optimizasyon
**TLDR:** A technique that limits gradient magnitude to prevent excessively large gradients from destabilizing training.

<p>Gradient clipping is used especially in deep and sequential networks to control the exploding gradient problem. When gradient values become excessively large, parameter updates can become unstable and training may break down. Clipping keeps those values within a defined range, enabling more controlled learning. It is a common safety mechanism in RNNs, transformer training, and large-scale deep learning experiments. This technique highlights that optimization is not only about speed, but also about stability.</p>