Backpropagation

Also known as: Backprop

Backpropagation computes gradients of the loss with respect to each parameter by applying the chain rule from output to input. Those gradients drive optimizers like SGD or Adam.

It is the workhorse training algorithm for deep networks, including transformers.

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