@inproceedings{
khaddaj2023extra,
title={Extra Training Provides a Strong Baseline for {CLIP}},
author={Alaa Khaddaj and Hadi Salman and Andrew Ilyas and Guillaume Leclerc and Aleksander Madry},
booktitle={R0-FoMo:Robustness of Few-shot and Zero-shot Learning in Large Foundation Models},
year={2023},
url={https://openreview.net/forum?id=v3JJmLYk12}
}
Contrastive Language-Image Pretraining (CLIP) models exhibit good performance on a range of vision tasks. To improve the performance of this class of models even further, several works have proposed to modify the CLIP training procedure. In this work, we show that it is possible to achieve substantial gains using a much simpler strategy. Specifically, existing CLIP models---especially those trained on smaller datasets---tend to be undertrained. As a result, simply extending the training procedure according to a simple heuristic can significantly improve the performance of CLIP models.
Extra Training Provides a Strong Baseline for CLIP
Alaa Khaddaj Hadi Salman Andrew Ilyas Guillaume Leclerc Aleksander Madry