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
The gist is that some measure of loss alongside the embedding would be tremendously useful, since the loss is a rough proxy of how good the model was creating the embedding.
It doesn't need to be the same loss as the training loss, a simpler one might be substantially faster than the actual loss we used for training (e.g. avoiding the DINO steps).
What is the simplest fastest loss we can generate alongside the embeddings?
The text was updated successfully, but these errors were encountered:
This reopens #207
The gist is that some measure of loss alongside the embedding would be tremendously useful, since the loss is a rough proxy of how good the model was creating the embedding.
It doesn't need to be the same loss as the training loss, a simpler one might be substantially faster than the actual loss we used for training (e.g. avoiding the DINO steps).
What is the simplest fastest loss we can generate alongside the embeddings?
The text was updated successfully, but these errors were encountered: