Awesome
realistic-ssl-evaluation-pytorch
This repository is reimplementation of Realistic Evaluation of Deep Semi-Supervised Learning Algorithms, by Avital Oliver*, Augustus Odena*, Colin Raffel*, Ekin D. Cubuk, and Ian J. Goodfellow, arXiv preprint arXiv:1804.09170. Original repo is here.
NOTE: This repository has been deprecated. Please see here, which includes UDA and FixMatch.
Requirements
- Python 3.6+
- PyTorch 1.1.0
- torchvision 0.3.0
- numpy 1.16.2
How to run
Prepare dataset
python build_dataset.py
Default setting is SVHN 1000 labels. If you try other settings, please check the options first by python build_dataset.py -h.
Running experiments
python train.py
Default setting is VAT. Please check the options by python python train.py -h
Performance
WIP
| algorithm | paper | this repo | ||
|---|---|---|---|---|
| cifar10 4k labels | svhn 1k labels | cifar10 4k labels | svhn 1k labels | |
| Supervised | 20.26 ±0.38 | 12.83 ±0.47 | 20.35±0.14 | 12.33±0.25 |
| Pi-Model | 16.37 ±0.63 | 7.19 ±0.27 | 16.24±0.38 | 7.81±0.39 |
| Mean Teacher | 15.87 ±0.28 | 5.65 ±0.47 | 15.77±0.22 | 6.48±0.44 |
| VAT | 13.86 ±0.27 | 5.63 ±0.20 | 13.83±0.49 | 5.84±0.20 |
| VAT+EM | 13.13 ±0.39 | 5.35 ±0.19 | 13.30±0.27 | 5.76±0.13 |
| Pseudo-Label | 17.78 ±0.57 | 7.62 ±0.29 | N/A | N/A |
| ICT | ( 7.66 ±0.17 ) | ( 3.53 ±0.07 ) | N/A | N/A |
| MixMatch | ( 6.50 ) | ( 3.27 ±0.31 ) | N/A | N/A |
NOTE: Experimental setting of ICT and MixMatch papers is different from this benchmark.
Reference
- Realistic Evaluation of Deep Semi-Supervised Learning Algorithms, by Avital Oliver*, Augustus Odena*, Colin Raffel*, Ekin D. Cubuk, and Ian J. Goodfellow, arXiv preprint arXiv:1804.09170.
- Interpolation Consistency Training for Semi-Supervised Learning, by Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
- MixMatch: A Holistic Approach to Semi-Supervised Learning, by David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel