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

  • Accurately
  • Efficiently
  • Quickly
  • Slowly
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.
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