early_stopping does not work as expected

[5tinzi]

Package Version

Flux v0.13.6

Julia Version

julia v1.7

OS / Environment

macOS 12.1 21C52 x86_64

Describe the bug

Flux has a function for early stopping, as describes in the documents page here: Utility Functions · Flux

For example, you can use early_stopping to stop training when the model is converging or deteriorating

By default distance is `-`, which implies that the monitored metric f is expected to be decreasing and minimized. 

But actually, the early_stop function will stop the train even if the loss is keeping decreasing!

Steps to Reproduce

julia> loss = let l = 10
         () -> l -= 1
       end; # NOTICE this loss function that returns decreasing values
julia> es = Flux.early_stopping(loss, 3);
julia> for i in 1:10
         @info "Epoch $i"
         es() && break
       end
[ Info: Epoch 1
[ Info: Epoch 2
[ Info: Epoch 3

Expected Results

the training won't be stop if the loss is keeping decreasing.

Observed Results

the training step was stop even the loss is keeping decreasing.

Relevant log output

No response

[5tinzi]

Close. Because this is not an bug.
a init_score needs to be specified and the default is 0, which is not always the case.
Sorry for my misunderstanding.