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optimizers

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Technology

Adam and AdamW: The Default Optimizer

Adam combines a first-order moment (a moving average of the gradient) and a second-order moment (an average of its squares) to give each parameter its own learning rate. With bias correction and the defaults β1=0.9, β2=0.999 and ε=1e-8, it converges fast with almost no tuning.

7 min
Technology

AdaGrad and RMSProp: Adaptive Learning Rates

AdaGrad and RMSProp are optimisers that give every weight its own learning rate. AdaGrad accumulates the square of all past gradients and divides the step by its root, which slowly fades it out. RMSProp fixes this with a moving average that forgets the past using a decay factor of about 0.9.

7 min