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early_stopping: <list[list[EarlyStopper]]> (Optional)

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Description

A list of potential early stopping strategies for AutoML to explore. An early stopping strategy can be empty in which case no early stopping is applied), or it can be configured through two parameters: min_delta and patience:
  • min_delta (default: 0.0): The minimum absolute change in the monitored tune metric to qualify as an improvement. Must be >= 0.0.
  • patience (default: 3): The number of epochs with no improvement after which training will be stopped. Must be > 0.
By default, training is stopped after 3 consecutive epochs with no improvements of the tune metric on the validation set.

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Supported Task Types

  • All

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Example

early_stopping:
- min_delta: 0.0
  patience: 3
- min_delta: 0.1
  patience: 0

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Default Values

early_stopping:
- min_delta: 0.0
  patience: 3