pub struct FineTuneSupervisedMethodHyperparameters {
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 FineTuneSupervisedMethodHyperparameters
impl<'de> Deserialize<'de> for FineTuneSupervisedMethodHyperparameters
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 FineTuneSupervisedMethodHyperparameters
impl RefUnwindSafe for FineTuneSupervisedMethodHyperparameters
impl Send for FineTuneSupervisedMethodHyperparameters
impl Sync for FineTuneSupervisedMethodHyperparameters
impl Unpin for FineTuneSupervisedMethodHyperparameters
impl UnwindSafe for FineTuneSupervisedMethodHyperparameters
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