The learning rate in an optimization algorithm affects how _______ the model converges to a minimum.

The learning rate determines how quickly the model converges during the training process. A low learning rate makes the model converge slowly, while a high learning rate may cause it to converge quickly but risk overshooting the minimum. Finding the right balance is crucial for training efficiency.