Update EarlyStopping docs (#7121)

Author: awaelchli

docs/source/common/early_stopping.rst

@@ -34,7 +34,7 @@ callback can be used to monitor a validation metric and stop the training when n
 To enable it:
 
 - Import :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping` callback.
-- Log the metric you want to monitor using :func:`~~pytorch_lightning.core.lightning.LightningModule.log` method.
+- Log the metric you want to monitor using :func:`~pytorch_lightning.core.lightning.LightningModule.log` method.
 - Init the callback, and set `monitor` to the logged metric of your choice.
 - Pass the :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping` callback to the :class:`~pytorch_lightning.trainer.trainer.Trainer` callbacks flag.
 
@@ -47,7 +47,7 @@ To enable it:
 
     trainer = Trainer(callbacks=[EarlyStopping(monitor='val_loss')])
 
--   You can customize the callbacks behaviour by changing its parameters.
+You can customize the callbacks behaviour by changing its parameters.
 
 .. testcode::
 
@@ -60,6 +60,15 @@ To enable it:
     )
     trainer = Trainer(callbacks=[early_stop_callback])
 
+
+Additional parameters that stop training at extreme points:
+
+- ``stopping_threshold``: Stops training immediately once the monitored quantity reaches this threshold.
+  It is useful when we know that going beyond a certain optimal value does not further benefit us.
+- ``divergence_threshold``: Stops training as soon as the monitored quantity becomes worse than this threshold.
+  When reaching a value this bad, we believe the model cannot recover anymore and it is better to stop early and run with different initial conditions.
+- ``check_finite``: When turned on, we stop training if the monitored metric becomes NaN or infinite.
+
 In case you need early stopping in a different part of training, subclass :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping`
 and change where it is called:
 
@@ -91,9 +100,3 @@ and change where it is called:
 .. seealso::
     - :class:`~pytorch_lightning.trainer.trainer.Trainer`
     - :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping`
-
-----------
-
-.. seealso::
-    - :class:`~pytorch_lightning.trainer.trainer.Trainer`
-    - :class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping`