In Adam, the weight decay is usually implemented by adding wd*w ( wd is weight decay here) to the gradients (Ist case), rather than actually ... ... <看更多>

I am using the ADAM optimizer at the moment with a learning rate of 0.001 and a weight decay value of 0.005. I understand that weight decay ... ... <看更多>

When weight decay is 0, there is no difference between Adam and AdamW. 0 Comments - powered by ... ... <看更多>

Decoupled Weight Decay Regularization (ICLR 2019). Contribute to loshchil/AdamW-and-SGDW development by creating an account on GitHub. ... <看更多>

There is no particular reason why we currently use the traditional weight decay form. I haven't experimented with AdamW style decay with MADGRAD yet. If you ... ... <看更多>

There is no particular reason why we currently use the traditional weight decay form. I haven't experimented with AdamW style decay with MADGRAD yet. If you ... ... <看更多>

I found Task using Adam as default optimizer, but afaik both Pytorch and Tensorflow has an wrong implementation of Adam w.r.t weight decay, so AdamW comes ... ... <看更多>

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01) --weight-decay WD Weight decay … MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer. 3D image classification from CT scans ... ... <看更多>