pub struct CreateFineTuningJobRequestHyperparameters {
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§
Source§impl<'de> Deserialize<'de> for CreateFineTuningJobRequestHyperparameters
impl<'de> Deserialize<'de> for CreateFineTuningJobRequestHyperparameters
Source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
Auto Trait Implementations§
impl Freeze for CreateFineTuningJobRequestHyperparameters
impl RefUnwindSafe for CreateFineTuningJobRequestHyperparameters
impl Send for CreateFineTuningJobRequestHyperparameters
impl Sync for CreateFineTuningJobRequestHyperparameters
impl Unpin for CreateFineTuningJobRequestHyperparameters
impl UnwindSafe for CreateFineTuningJobRequestHyperparameters
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more