Hyperparameter Sweep

Definitions

1. A systematic run of many training jobs with different hyperparameter settings, such as learning rate or batch size, to find stronger model performance.

   In plain English: Testing many model settings to see which combination works best.

   Example: "We ran a hyperparameter sweep overnight to find a stable training setup."

Related Terms

• Active Learning
• Adaptive Learning Rate
• Adversarial Training
• Batch Size
• Curriculum Learning
• Deep Learning
• Deep Reinforcement Learning
• Distributed Training
• Multivariate Testing