Struct TrainingConfig 

pub struct TrainingConfig {
    pub epochs: usize,
    pub batch_size: usize,
    pub gradient_accumulation_steps: usize,
    pub learning_rate: f64,
    pub lr_scheduler: LrScheduler,
    pub warmup_ratio: f32,
    pub weight_decay: f64,
    pub max_grad_norm: f32,
    pub save_steps: usize,
    pub logging_steps: usize,
    pub gradient_checkpointing: bool,
    pub mixed_precision: bool,
}

Training hyperparameters.

Example

use axolotl_rs::TrainingConfig;
use axolotl_rs::config::LrScheduler;

let training = TrainingConfig {
    epochs: 3,
    batch_size: 4,
    learning_rate: 2e-4,
    lr_scheduler: LrScheduler::Cosine,
    warmup_ratio: 0.03,
    gradient_accumulation_steps: 4,
    ..Default::default()
};

assert_eq!(training.epochs, 3);
assert_eq!(training.batch_size, 4);

Fields

epochs: usize

Number of training epochs.

batch_size: usize

Batch size per device.

gradient_accumulation_steps: usize

Gradient accumulation steps.

learning_rate: f64

Learning rate.

lr_scheduler: LrScheduler

Learning rate scheduler.

warmup_ratio: f32

Warmup ratio.

weight_decay: f64

Weight decay.

max_grad_norm: f32

Maximum gradient norm for clipping.

save_steps: usize

Save checkpoint every N steps.

logging_steps: usize

Log every N steps.

gradient_checkpointing: bool

Use gradient checkpointing.

mixed_precision: bool

Use mixed precision training.

Trait Implementations

impl Clone for TrainingConfig

fn clone(&self) -> TrainingConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TrainingConfig

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

Formats the value using the given formatter.

impl Default for TrainingConfig

fn default() -> TrainingConfig

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for TrainingConfig

fn deserialize<__D>( __deserializer: __D, ) -> Result<TrainingConfig, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for TrainingConfig

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

where __S: Serializer,

Serialize this value into the given Serde serializer.