final case class CreateFineTuningJobRequest(model: CreateFineTuningJobRequest.Model, trainingFile: String, hyperparameters: Optional[Hyperparameters] = Optional.Absent, suffix: Optional[Suffix] = Optional.Absent, validationFile: Optional[String] = Optional.Absent) extends Product with Serializable

CreateFineTuningJobRequest model

model

The name of the model to fine-tune. You can select one of the [supported models](/docs/guides/fine-tuning/what-models-can-be-fine-tuned).

trainingFile

The ID of an uploaded file that contains training data. See [upload file](/docs/api-reference/files/upload) for how to upload a file. Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose fine-tune. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.

hyperparameters

The hyperparameters used for the fine-tuning job.

suffix

A string of up to 18 characters that will be added to your fine-tuned model name. For example, a suffix of "custom-model-name" would produce a model name like ft:gpt-3.5-turbo:openai:custom-model-name:7p4lURel.

validationFile

The ID of an uploaded file that contains validation data. If you provide this file, the data is used to generate validation metrics periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. The same data should not be present in both train and validation files. Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.

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Instance Constructors

  1. new CreateFineTuningJobRequest(model: CreateFineTuningJobRequest.Model, trainingFile: String, hyperparameters: Optional[Hyperparameters] = Optional.Absent, suffix: Optional[Suffix] = Optional.Absent, validationFile: Optional[String] = Optional.Absent)

    model

    The name of the model to fine-tune. You can select one of the [supported models](/docs/guides/fine-tuning/what-models-can-be-fine-tuned).

    trainingFile

    The ID of an uploaded file that contains training data. See [upload file](/docs/api-reference/files/upload) for how to upload a file. Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose fine-tune. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.

    hyperparameters

    The hyperparameters used for the fine-tuning job.

    suffix

    A string of up to 18 characters that will be added to your fine-tuned model name. For example, a suffix of "custom-model-name" would produce a model name like ft:gpt-3.5-turbo:openai:custom-model-name:7p4lURel.

    validationFile

    The ID of an uploaded file that contains validation data. If you provide this file, the data is used to generate validation metrics periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. The same data should not be present in both train and validation files. Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.

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  9. val hyperparameters: Optional[Hyperparameters]
  10. final def isInstanceOf[T0]: Boolean
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  11. val model: CreateFineTuningJobRequest.Model
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  15. def productElementNames: Iterator[String]
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  16. val suffix: Optional[Suffix]
  17. final def synchronized[T0](arg0: => T0): T0
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  18. val trainingFile: String
  19. val validationFile: Optional[String]
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