feat: integrate new loss and pooling options #664
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i feel the name |
LMMilliken
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the documentation is not included in the docs anymore, please double check |
Ah, I forgot to update the index when I renamed the file, fixed now |
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| SphereFace loss is a loss function that was first formulated for computer vision and face recognition tasks. | ||
| Finetuner supports two variations of this loss function, `ArcFaceLoss` and `CosFaceLoss`. | ||
| Instead of attempting to minimise the distance between positive pairs and maximise the distance between negative pairs, the SphereFace loss functions compare each sample with the center of each class |
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| Instead of attempting to minimise the distance between positive pairs and maximise the distance between negative pairs, the SphereFace loss functions compare each sample with the center of each class | |
| Instead of attempting to minimise the distance between positive pairs and maximise the distance between negative pairs, the SphereFace loss functions compare each sample with the center of each class |
I think here it is confusing what is the center of a class ?
In practice this is not really center but more estimated prototypes which is learn alongside the representation in the last linear softmax layer. Not sure how to put it in nice word so I let you the burden
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I have changed it to '...with an estimate of the center point of each classes' embeddings.'
I don't want to go into too much detail explaining it but i think this is more accurate
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📝 Docs are deployed on https://ft-feat-support-arcface--jina-docs.netlify.app 🎉 |
This pr adds support for the newly added loss and pooling options from core, as well as a new page in the documentation explaining how to use them.