I noted that the 15M subset of YFCC you use is significantly different from the subset that OpenAI uses and the Quality not Quantity paper uses. To compare the proportion of matching samples, I just did a quick test and saw that the overall stats for the three datasets are:
The difference between the quality-not-quantity and openai csvs can simply be attributed to link rot.
Further, when I take an intersection between your photo-ids and the photo-ids used by OpenAI / Quality not Quantity:
declip intersection with openai: 6,642,077 matches
declip intersection with quality-not-quantity: 6,640,264 matches
It is interesting that there are still so many matches (~40%). I just wanted to add this information here since I found it quite hard to figure out the exact differences and intersections between the different YFCC subsets. So in-case people are trying to use YFCC15M subsets based on the OpenAI-CLIP subsets, this is useful to keep in mind that the DeCLIP subset is substantially different. This is also mentioned in the DeCLIP paper, appendix F and table 8.
Hey,
Thanks for the great work.
I noted that the 15M subset of YFCC you use is significantly different from the subset that OpenAI uses and the Quality not Quantity paper uses. To compare the proportion of matching samples, I just did a quick test and saw that the overall stats for the three datasets are:
The difference between the quality-not-quantity and openai csvs can simply be attributed to link rot.
Further, when I take an intersection between your photo-ids and the photo-ids used by OpenAI / Quality not Quantity:
It is interesting that there are still so many matches (~40%). I just wanted to add this information here since I found it quite hard to figure out the exact differences and intersections between the different YFCC subsets. So in-case people are trying to use YFCC15M subsets based on the OpenAI-CLIP subsets, this is useful to keep in mind that the DeCLIP subset is substantially different. This is also mentioned in the DeCLIP paper, appendix F and table 8.