pub struct FineTuneDpoMethodHyperparameters {
pub batch_size: Option<Value>,
pub beta: 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.
beta: Option<Value>
The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model.
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 FineTuneDpoMethodHyperparameters
impl<'de> Deserialize<'de> for FineTuneDpoMethodHyperparameters
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 FineTuneDpoMethodHyperparameters
impl RefUnwindSafe for FineTuneDpoMethodHyperparameters
impl Send for FineTuneDpoMethodHyperparameters
impl Sync for FineTuneDpoMethodHyperparameters
impl Unpin for FineTuneDpoMethodHyperparameters
impl UnwindSafe for FineTuneDpoMethodHyperparameters
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