Updated EarlyStopping in rst doc

docs/source/early_stopping.rst

@@ -13,34 +13,44 @@ By default early stopping will be enabled if `'val_loss'`
 is found in :meth:`~pytorch_lightning.core.lightning.LightningModule.validation_epoch_end`'s
 return dict. Otherwise training will proceed with early stopping disabled.
 
-Enable Early Stopping using Callbacks on epoch end
---------------------------------------------------
-There are two ways to enable early stopping using callbacks on epoch end.
+Enable Early Stopping using the EarlyStopping Callback
+------------------------------------------------------
+The 
+:class:`~pytorch_lightning.callbacks.early_stopping.EarlyStopping`
+callback can be used to monitor a validation metric and stop the training when no improvement is observed.
+
+There are two ways to enable the EarlyStopping callback:
 
 .. doctest::
 
     >>> from pytorch_lightning import Trainer
     >>> from pytorch_lightning.callbacks import EarlyStopping
 
-    # A) Set early_stop_callback to True. Will look for 'val_loss'
-    # in validation_epoch_end() return dict. If it is not found an error is raised.
+    # A) Set early_stop_callback=True. 
+    # The callback will look for 'val_loss' in the dict returned by validation_epoch_end(). 
+    # If `val_loss` is not found an error is raised.
     >>> trainer = Trainer(early_stop_callback=True)
-    # B) Or configure your own callback
+    # B) Create the callback object and pass it to the trainer.
+    # This allows for further customization of the callback.
     >>> early_stop_callback = EarlyStopping(
-    ...    monitor='val_loss',
+    ...    monitor='val_accuracy',
     ...    min_delta=0.00,
     ...    patience=3,
     ...    verbose=False,
-    ...    mode='min'
+    ...    mode='max'
     ... )
     >>> trainer = Trainer(early_stop_callback=early_stop_callback)
 
-In any case, the callback will fall back to the training metrics (returned in
-:meth:`~pytorch_lightning.core.lightning.LightningModule.training_step`,
-:meth:`~pytorch_lightning.core.lightning.LightningModule.training_step_end`)
-looking for a key to monitor if validation is disabled or
-:meth:`~pytorch_lightning.core.lightning.LightningModule.validation_epoch_end`
-is not defined.
+.. note::
+   The EarlyStopping callback runs at the end of every validation epoch, 
+   which, under the default configuration, happen after every training epoch.
+   However, the frequency of validation can be modified by setting various parameters on the
+   :class:`~pytorch_lightning.trainer.trainer.Trainer`
+   , for example `check_val_every_n_epoch` and `val_check_interval`.
+   It must be noted that the `patience` parameter counts the number of 
+   validation epochs with no improvement, and not the number of training epochs.
+   Therefore, with parameters `check_val_every_n_epoch=10` and `patience=3`, the trainer
+   will perform at least 40 training epochs before being stopped.
 
 .. seealso::
     :class:`~pytorch_lightning.trainer.trainer.Trainer`