All Implemented Interfaces:


public final class FineTuningJob.Method.Dpo.Hyperparameters

The hyperparameters used for the fine-tuning job.

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description
`public final class`	`FineTuningJob.Method.Dpo.Hyperparameters.Builder`	A builder for Hyperparameters.
`public final class`	`FineTuningJob.Method.Dpo.Hyperparameters.BatchSize`	Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
`public final class`	`FineTuningJob.Method.Dpo.Hyperparameters.Beta`	The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
`public final class`	`FineTuningJob.Method.Dpo.Hyperparameters.LearningRateMultiplier`	Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
`public final class`	`FineTuningJob.Method.Dpo.Hyperparameters.NEpochs`	The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

Field Summary

Fields
Modifier and Type	Field	Description

Constructor Summary

Constructors
Constructor	Description

Enum Constant Summary

Enum Constants
Enum Constant	Description

Method Summary

Modifier and Type	Method	Description
`final Optional<FineTuningJob.Method.Dpo.Hyperparameters.BatchSize>`	`batchSize()`	Number of examples in each batch.
`final Optional<FineTuningJob.Method.Dpo.Hyperparameters.Beta>`	`beta()`	The beta value for the DPO method.
`final Optional<FineTuningJob.Method.Dpo.Hyperparameters.LearningRateMultiplier>`	`learningRateMultiplier()`	Scaling factor for the learning rate.
`final Optional<FineTuningJob.Method.Dpo.Hyperparameters.NEpochs>`	`nEpochs()`	The number of epochs to train the model for.
`final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.BatchSize>`	`_batchSize()`	Number of examples in each batch.
`final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.Beta>`	`_beta()`	The beta value for the DPO method.
`final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.LearningRateMultiplier>`	`_learningRateMultiplier()`	Scaling factor for the learning rate.
`final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.NEpochs>`	`_nEpochs()`	The number of epochs to train the model for.
`final Map<String, JsonValue>`	`_additionalProperties()`
`final FineTuningJob.Method.Dpo.Hyperparameters`	`validate()`
`final FineTuningJob.Method.Dpo.Hyperparameters.Builder`	`toBuilder()`
`Boolean`	`equals(Object other)`
`Integer`	`hashCode()`
`String`	`toString()`
`final static FineTuningJob.Method.Dpo.Hyperparameters.Builder`	`builder()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
- Method Detail
  - batchSize
```
 final Optional<FineTuningJob.Method.Dpo.Hyperparameters.BatchSize> batchSize()
```
    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
  - beta
```
 final Optional<FineTuningJob.Method.Dpo.Hyperparameters.Beta> beta()
```
    The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
  - learningRateMultiplier
```
 final Optional<FineTuningJob.Method.Dpo.Hyperparameters.LearningRateMultiplier> learningRateMultiplier()
```
    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
  - nEpochs
```
 final Optional<FineTuningJob.Method.Dpo.Hyperparameters.NEpochs> nEpochs()
```
    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
  - _batchSize
```
 final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.BatchSize> _batchSize()
```
    Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance.
  - _beta
```
 final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.Beta> _beta()
```
    The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
  - _learningRateMultiplier
```
 final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.LearningRateMultiplier> _learningRateMultiplier()
```
    Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
  - _nEpochs
```
 final JsonField<FineTuningJob.Method.Dpo.Hyperparameters.NEpochs> _nEpochs()
```
    The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.
  - _additionalProperties
```
 final Map<String, JsonValue> _additionalProperties()
```
  - validate
```
 final FineTuningJob.Method.Dpo.Hyperparameters validate()
```
  - toBuilder
```
 final FineTuningJob.Method.Dpo.Hyperparameters.Builder toBuilder()
```
  - equals
```
 Boolean equals(Object other)
```
  - hashCode
```
 Integer hashCode()
```
  - toString
```
 String toString()
```
  - builder
```
 final static FineTuningJob.Method.Dpo.Hyperparameters.Builder builder()
```

Class FineTuningJob.Method.Dpo.Hyperparameters

Nested Class Summary

Field Summary

Constructor Summary

Enum Constant Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Method Detail

batchSize

beta

learningRateMultiplier

nEpochs

_batchSize

_beta

_learningRateMultiplier

_nEpochs

_additionalProperties

validate

toBuilder

equals

hashCode

toString

builder