This project is a Pytorch implementation from scratch of the paper Barlow Twins: Self-Supervised Learning via Redundancy Reduction
@article{zbontar2021barlow,
title={Barlow Twins: Self-Supervised Learning via Redundancy Reduction},
author={Zbontar, Jure and Jing, Li and Misra, Ishan and LeCun, Yann and Deny, St{\'e}phane},
journal={arXiv preprint arXiv:2103.03230},
year={2021}
}
This model was trained with the CIFAR training set during 170 epochs . It was then evaluated on the CIFAR validation set by a linear layer trained on top of a frozen Barlow Twins model.
- Training was done on Tesla P100-PCIE-16GB and takes around 1:40 min per epoch
Work is still in progress, here are the current results:
| Epochs | Batch Size | Top1 Acc |
|---|---|---|
| 170 | 256 | 66.32 |
This work was inspired by the Facebook Research Github Repository for Barlow Twins