19 июл. 2022 г. · I'm using PyTorch lightning to handle the optimisation but I assume the problem lies in incompatibility of ReduceLROnPlateau with SequentialLR.

Warmup learning rate until `warmup_steps` and reduce learning rate on plateau after. Args: optimizer (Optimizer): wrapped optimizer.

Models often benefit from reducing the learning rate by a factor of 2-10 once learning stagnates. This scheduler reads a metrics quantity and if no improvement ...

Gradually warm-up(increasing) learning rate in optimizer. Proposed in 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour'.

23 февр. 2021 г. · Generally, I can confirm from many experiments that reducing LR on plateau can help a lot even with adaptive optimizers like Adam. Keras callback ReduceLROnPlateau - cooldown parameter Can ReduceLrOnPlateau scheduler in pytorch use test set ... PyTorch Lightning's ReduceLRonPlateau not working properly Custom callbacks with warm up and cosine decay in TensorFlow Другие результаты с сайта stackoverflow.com

To do more interesting things with your optimizers such as learning rate warm-up or odd scheduling, override the optimizer_step() function.

2 июн. 2024 г. · LS, I have a question regarding the behaviour of the ReduceLROnPlateau scheduler in combination with the Adam optimiser.

Initializes the ReduceLROnPlateau object. This scheduler decreases the learning rate when a metric has stopped improving, which is commonly used to fine-tune a ...

9 апр. 2024 г. · ReduceLROnPlateau is a scheduling technique that decreases the learning rate when the specified metric stops improving for longer than the patience number ...

This function will pass the arguments to ReduceLROnPlateau if the warmup is done, and call `self.batch_step` if the warm-up is per epoch, to update the LR.