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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- 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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- val batchSize: Optional[BatchSize]
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