Pytorch implementation of Learning Rate Dropout.

Last update: Nov 25, 2022

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Deep Learning Learning-Rate-Dropout

Overview

Learning-Rate-Dropout

Pytorch implementation of Learning Rate Dropout.

Paper Link: https://arxiv.org/pdf/1912.00144.pdf

Train ResNet-34 for Cifar10:

run:

python main.py --model=resnet --optim=adam_lrd --lr=0.001 --LRD_p=0.5

python main.py --model=resnet --optim=adam --lr=0.001

python main.py --model=resnet --optim=sgd_lrd --lr=0.1 --LRD_p=0.5

python main.py --model=resnet --optim=sgd --lr=0.1 

python main.py --model=resnet --optim=rmsprop_lrd --lr=0.001 --LRD_p=0.5

python main.py --model=resnet --optim=rmsprop --lr=0.001

After training, run "plot.py" to show the learning curves.

Owner

GitHub Repository

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Pytorch implementation of Learning Rate Dropout.

Related tags

Overview

Learning-Rate-Dropout

Owner

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