Fixes as per Grammarly

Author: svilupp

docs/src/utilities.md

@@ -122,7 +122,7 @@ Flux.skip
 
 Flux provides utilities for controlling your training procedure according to some monitored condition and a maximum `patience`. For example, you can use `early_stopping` to stop training when the model is converging or deteriorating, or you can use `plateau` to check if the model is stagnating.
 
-For example, below we create a pseudo-loss function that decreases, bottoms out, then increases. The early stopping trigger will break the loop before the loss increases too much.
+For example, below we create a pseudo-loss function that decreases, bottoms out, and then increases. The early stopping trigger will break the loop before the loss increases too much.
 ```julia
 # create a pseudo-loss that decreases for 4 calls, then starts increasing
 # we call this like loss()
@@ -143,7 +143,7 @@ es = early_stopping(loss, 2; init_score = 9)
 end
 ```
 
-The keyword argument `distance` of `early_stopping` is a function of the form `distance(best_score, score)`. By default `distance` is `-`, which implies that the monitored metric `f` is expected to be decreasing and mimimized. If you use some increasing metric (e.g. accuracy), you can customize the `distance` function: `(best_score, score) -> score - best_score`.
+The keyword argument `distance` of `early_stopping` is a function of the form `distance(best_score, score)`. By default `distance` is `-`, which implies that the monitored metric `f` is expected to be decreasing and minimized. If you use some increasing metric (e.g. accuracy), you can customize the `distance` function: `(best_score, score) -> score - best_score`.
 ```julia
 # create a pseudo-accuracy that increases by 0.01 each time from 0 to 1
 # we call this like acc()