Over9000 optimizer

Overview

Optimizers and tests

Every result is avg of 20 runs.

Dataset LR Schedule Imagenette size 128, 5 epoch Imagewoof size 128, 5 epoch
Adam - baseline OneCycle 0.8493 0.6125
RangerLars (RAdam + LARS + Lookahead) Flat and anneal 0.8732 0.6523
Ralamb (RAdam + LARS) Flat and anneal 0.8675 0.6367
Ranger (RAdam + Lookahead) Flat and anneal 0.8594 0.5946
Novograd Flat and anneal 0.8711 0.6126
Radam Flat and anneal 0.8444 0.537
Lookahead OneCycle 0.8578 0.6106
Lamb OneCycle 0.8400 0.5597
DiffGrad OneCycle 0.8527 0.5912
AdaMod OneCycle 0.8473 0.6132
Owner
Mikhail Grankin
Mikhail Grankin
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Over9000 optimizer

Optimizers and tests Every result is avg of 20 runs. Dataset LR Schedule Imagenette size 128, 5 epoch Imagewoof size 128, 5 epoch Adam - baseline OneC

Mikhail Grankin 405 Nov 27, 2022
Learning Sparse Neural Networks through L0 regularization

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Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute

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