Adam
struct
defined in module
Flux.Optimise
Adam(η = 0.001, β::Tuple = (0.9, 0.999), ϵ = 1.0e-8)
Adam optimiser.
Learning rate (
η
): Amount by which gradients are discounted before updating the weights.
Decay of momentums (
β::Tuple
): Exponential decay for the first (β1) and the second (β2) momentum estimate.
opt
=
Adam
(
)
opt
=
Adam
(
0.001
,
(
0.9
,
0.8
)
)
There are
3
methods for Flux.Optimise.Adam
:
The following pages link back here:
Custom learning tasks, Image segmentation, Introduction, Keypoint regression, Siamese image similarity
Flux.jl , deprecations.jl , optimise/Optimise.jl , optimise/optimisers.jl