Over9000 optimizer

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Deep Learningover9000
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
GitHub Repository
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt.

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Code for MarioNette: Self-Supervised Sprite Learning, in NeurIPS 2021

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MG-GCN: Scalable Multi-GPU GCN Training Framework

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CUDA Python Low-level Bindings

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Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensors, CVPR 2021

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RP-GAN: Stable GAN Training with Random Projections

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Pytorch implementation of Masked Auto-Encoder

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Implementation of Pix2Seq in PyTorch

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Real time Human Detection Counting

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Group Fisher Pruning for Practical Network Compression(ICML2021)

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The 3rd place solution for competition

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DGN pymarl - Implementation of DGN on Pymarl, which could be trained by VDN or QMIX

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