Struct FineTuningJobHyperparameters

pub struct FineTuningJobHyperparameters {
    pub batch_size: Option<Value>,
    pub learning_rate_multiplier: Option<Value>,
    pub n_epochs: Option<Value>,
}

Fields

batch_size: Option<Value>

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

learning_rate_multiplier: Option<Value>

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

n_epochs: Option<Value>

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

Trait Implementations

impl Debug for FineTuningJobHyperparameters

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for FineTuningJobHyperparameters

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for FineTuningJobHyperparameters

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.