LearningRateFinder

class lib.training.lr_finder.LearningRateFinder(trainer: train.Trainer, scheduler: ExponentialLR, steps: int, strength: T.Literal['default', 'aggressive', 'extreme'], mode: T.Literal['set', 'graph_and_set', 'graph_and_exit'], stop_factor: int = 4, beta: float = 0.98)

Bases: object

Learning Rate Finder

Parameters:

  • trainer (train.Trainer) – The training loop with the loaded training plugin

  • scheduler (ExponentialLR) – The LRFinder scheduler

  • steps (int) – The number of steps to run the finder for

  • strength (T.Literal['default', 'aggressive', 'extreme']) – How aggressively to set the optimal learning rate

  • mode (T.Literal['set', 'graph_and_set', 'graph_and_exit']) – The mode to run the Learning Rate Finder in

  • stop_factor (int) – When to stop finding the optimal learning rate

  • beta (float) – Amount to smooth loss by, for graphing purposes

Attributes Summary

best_lr

The discovered best learning rate or None if not found

Methods Summary

find()

Find the optimal learning rate

Attributes Documentation

best_lr

The discovered best learning rate or None if not found

Methods Documentation

find() → None

Find the optimal learning rate

Return type:

None

property best_lr: None | float

The discovered best learning rate or None if not found

find() → None

Find the optimal learning rate

Return type:

None