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final case class Hyperparameters(batchSize: Optional[BatchSize] = Optional.Absent, learningRateMultiplier: Optional[LearningRateMultiplier] = Optional.Absent, nEpochs: Optional[NEpochs] = Optional.Absent) extends Product with Serializable

hyperparameters model

The hyperparameters used for the fine-tuning job.

batchSize

Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.

learningRateMultiplier

Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.

nEpochs

The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

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  1. new Hyperparameters(batchSize: Optional[BatchSize] = Optional.Absent, learningRateMultiplier: Optional[LearningRateMultiplier] = Optional.Absent, nEpochs: Optional[NEpochs] = Optional.Absent)

    batchSize

    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.

    learningRateMultiplier

    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.

    nEpochs

    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

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  5. val batchSize: Optional[BatchSize]
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  11. val learningRateMultiplier: Optional[LearningRateMultiplier]
  12. val nEpochs: Optional[NEpochs]
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