https://github.com/YU1ut/MixMatch-pytorch
Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"
https://github.com/YU1ut/MixMatch-pytorch
deep-learning pytorch semi-supervised-learning
Last synced: about 1 year ago
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Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"
- Host: GitHub
- URL: https://github.com/YU1ut/MixMatch-pytorch
- Owner: YU1ut
- License: mit
- Created: 2019-05-22T03:22:19.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-11-02T15:46:45.000Z (over 2 years ago)
- Last Synced: 2024-08-04T03:11:07.051Z (almost 2 years ago)
- Topics: deep-learning, pytorch, semi-supervised-learning
- Language: Python
- Size: 20.5 KB
- Stars: 630
- Watchers: 12
- Forks: 129
- Open Issues: 27
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# MixMatch
This is an unofficial PyTorch implementation of [MixMatch: A Holistic Approach to Semi-Supervised Learning](https://arxiv.org/abs/1905.02249).
The official Tensorflow implementation is [here](https://github.com/google-research/mixmatch).
Now only experiments on CIFAR-10 are available.
This repository carefully implemented important details of the official implementation to reproduce the results.
## Requirements
- Python 3.6+
- PyTorch 1.0
- **torchvision 0.2.2 (older versions are not compatible with this code)**
- tensorboardX
- progress
- matplotlib
- numpy
## Usage
### Train
Train the model by 250 labeled data of CIFAR-10 dataset:
```
python train.py --gpu --n-labeled 250 --out cifar10@250
```
Train the model by 4000 labeled data of CIFAR-10 dataset:
```
python train.py --gpu --n-labeled 4000 --out cifar10@4000
```
### Monitoring training progress
```
tensorboard.sh --port 6006 --logdir cifar10@250
```
## Results (Accuracy)
| #Labels | 250 | 500 | 1000 | 2000| 4000 |
|:---|:---:|:---:|:---:|:---:|:---:|
|Paper | 88.92 ± 0.87 | 90.35 ± 0.94 | 92.25 ± 0.32| 92.97 ± 0.15 |93.76 ± 0.06|
|This code | 88.71 | 88.96 | 90.52 | 92.23 | 93.52 |
(Results of this code were evaluated on 1 run. Results of 5 runs with different seeds will be updated later. )
## References
```
@article{berthelot2019mixmatch,
title={MixMatch: A Holistic Approach to Semi-Supervised Learning},
author={Berthelot, David and Carlini, Nicholas and Goodfellow, Ian and Papernot, Nicolas and Oliver, Avital and Raffel, Colin},
journal={arXiv preprint arXiv:1905.02249},
year={2019}
}
```