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Update "Composing Optimisers" docs #1628

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Jun 24, 2021
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Update "Composing Optimisers" docs #1628

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2 changes: 1 addition & 1 deletion docs/src/training/optimisers.md
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Expand Up @@ -107,7 +107,7 @@ Flux defines a special kind of optimiser simply called `Optimiser` which takes i
that will be fed into the next, and the resultant update will be applied to the parameter as usual. A classic use case is where adding decays is desirable. Flux defines some basic decays including `ExpDecay`, `InvDecay` etc.

```julia
opt = Optimiser(ExpDecay(0.001, 0.1, 1000, 1e-4), Descent())
opt = Optimiser(ExpDecay(1, 0.1, 1000, 1e-4), Descent())
```

Here we apply exponential decay to the `Descent` optimiser. The defaults of `ExpDecay` say that its learning rate will be decayed every 1000 steps.
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