convergence

A state reached when loss values change very little or not at all with each iteration. For example, the following loss curve suggests convergence at around 700 iterations: A model converges when additional training won't improve the model. In deep learning, loss values sometimes stay constant or nearly so for many iterations before finally descending. During a long period of constant loss values, you may temporarily get a false sense of convergence. See also early stopping. See Model convergence and loss curves in Machine Learning Crash Course for more information.

Practitioners refer to convergence when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.