Make it clearer that losses reduce along the batch dimension (#2004)

Fixes keras-team/keras#20395.

templates/api/losses/index.md

@@ -76,7 +76,8 @@ A loss is a callable with arguments `loss_fn(y_true, y_pred, sample_weight=None)
     by the corresponding value of `sample_weight`. (Note on`dN-1`: all loss
     functions reduce by 1 dimension, usually `axis=-1`.)
 
-By default, loss functions return one scalar loss value per input sample, e.g.
+By default, loss functions return one scalar loss value for each input sample
+in the batch dimension, e.g.
 
 ```
 >>> from keras import ops