Hyperparameters class final

Hyperparameters controlling the tuning process. Read more at https://ai.google.dev/docs/model_tuning_guidance

Inheritance

Constructors

Hyperparameters({double? learningRate, double? learningRateMultiplier, int? epochCount, int? batchSize})
Hyperparameters.fromJson(Object? j): factory

batchSize → int?: Immutable. The batch size hyperparameter for tuning. If not set, a default of 4 or 16 will be used based on the number of training examples.
final
epochCount → int?: Immutable. The number of training epochs. An epoch is one pass through the training data. If not set, a default of 5 will be used.
final
hashCode → int: The hash code for this object.
no setterinherited
learningRate → double?: Optional. Immutable. The learning rate hyperparameter for tuning. If not set, a default of 0.001 or 0.0002 will be calculated based on the number of training examples.
final
learningRateMultiplier → double?: Optional. Immutable. The learning rate multiplier is used to calculate a final learning_rate based on the default (recommended) value. Actual learning rate := learning_rate_multiplier * default learning rate Default learning rate is dependent on base model and dataset size. If not set, a default of 1.0 will be used.
final
qualifiedName → String: The fully qualified name of this message, i.e., google.protobuf.Duration or google.rpc.ErrorInfo.
finalinherited
runtimeType → Type: A representation of the runtime type of the object.
no setterinherited

noSuchMethod(Invocation invocation) → dynamic: Invoked when a nonexistent method or property is accessed.
inherited
toJson() → Object: override
toString() → String: A string representation of this object.
override