m = β1·m + (1−β1)·g              β1 = 0.9      (average gradient)
v = β2·v + (1−β2)·g²             β2 = 0.999    (average squared gradient)

m̂ = m / (1 − β1^t)               bias correction, t = step number
v̂ = v / (1 − β2^t)

param = param − lr · m̂ / (√v̂ + ε)