You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello
Thanks for sharing the e-commerce embedding model thats beating SOTA by a nice margin.
I wanted to understand how are the e-commerce embeddings different from Marqo Siglip trained earlier from a metric standpoint.
Did you ever do a comparison on same data for retrieval/search?
The text was updated successfully, but these errors were encountered:
Hi @aretius , there are a few differences. The main differences were the data sets. FashionSigLIP was trained with a smaller but richer dataset. This also changed how the loss was done between the two models. We used 7 text fields and 1 image field so the loss was all combinations of img and text as well as the mean of the text vectors (i.e. fused).
Hello
Thanks for sharing the e-commerce embedding model thats beating SOTA by a nice margin.
I wanted to understand how are the e-commerce embeddings different from Marqo Siglip trained earlier from a metric standpoint.
Did you ever do a comparison on same data for retrieval/search?
The text was updated successfully, but these errors were encountered: