datacomp
This competition aims to design effective datasets for pre-training CLIP models, prioritizing dataset curation. Participants focus on achieving high accuracy in downstream tasks by selecting optimal image-text pairs, with a fixed model setup. The competition offers two tracks, allowing varying computational resources: one with a provided data pool and another that accepts additional external data. With scales from small to xlarge, it covers different computational demands. The project offers tools for downloading, selecting subsets, training, and evaluation to support flexible and robust participation.
