Package com.google.genai.types

Class CreateTuningJobConfig

java.lang.Object
com.google.genai.JsonSerializable
com.google.genai.types.CreateTuningJobConfig
public abstract class CreateTuningJobConfig extends JsonSerializable
Supervised fine-tuning job creation request - optional fields.

  • Constructor Details

    • CreateTuningJobConfig

      public CreateTuningJobConfig()

  • Method Details

    • httpOptions

      public abstract Optional<HttpOptions> httpOptions()
      Used to override HTTP request options.

    • validationDataset

      public abstract Optional<TuningValidationDataset> validationDataset()
      Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.

    • tunedModelDisplayName

      public abstract Optional<String> tunedModelDisplayName()
      The display name of the tuned Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.

    • description

      public abstract Optional<String> description()
      The description of the TuningJob

    • epochCount

      public abstract Optional<Integer> epochCount()
      Number of complete passes the model makes over the entire training dataset during training.

    • learningRateMultiplier

      public abstract Optional<Float> learningRateMultiplier()
      Multiplier for adjusting the default learning rate.

    • exportLastCheckpointOnly

      public abstract Optional<Boolean> exportLastCheckpointOnly()
      If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT.

    • preTunedModelCheckpointId

      public abstract Optional<String> preTunedModelCheckpointId()
      The optional checkpoint id of the pre-tuned model to use for tuning, if applicable.

    • adapterSize

      public abstract Optional<AdapterSize> adapterSize()
      Adapter size for tuning.

    • batchSize

      public abstract Optional<Integer> batchSize()
      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.

    • learningRate

      public abstract Optional<Float> learningRate()
      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.

    • builder

      public static CreateTuningJobConfig.Builder builder()
      Instantiates a builder for CreateTuningJobConfig.

    • toBuilder

      public abstract CreateTuningJobConfig.Builder toBuilder()
      Creates a builder with the same values as this instance.

    • fromJson

      public static CreateTuningJobConfig fromJson(String jsonString)
      Deserializes a JSON string to a CreateTuningJobConfig object.