Apply suggestions from code review

Co-authored-by: Adrian Wälchli <[email protected]>

Author: rohitgr7

docs/source/common/debugging.rst

@@ -79,7 +79,7 @@ argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 
 .. testcode::
 
-    # use only 1% of training data (and turn-off validation)
+    # use only 1% of training data (and turn off validation)
     trainer = Trainer(overfit_batches=0.01)
 
     # similar, but with a fixed 10 batches

docs/source/common/trainer.rst

@@ -1074,7 +1074,7 @@ overfit_batches
 
 |
 
-Uses this much data of the training set. If nonzero, will turn-off validation.
+Uses this much data of the training set. If nonzero, will turn off validation.
 If the training dataloaders have `shuffle=True`, Lightning will automatically disable it.
 
 Useful for quickly debugging or trying to overfit on purpose.

docs/source/guides/speed.rst

@@ -336,7 +336,7 @@ If you don't want to check 100% of the training/validation/test set set these fl
 
 If you also pass ``shuffle=True`` to the dataloader, a different random subset of your dataset will be used for each epoch; otherwise the same subset will be used for all epochs.
 
-.. note:: ``limit_train_batches`` will be overwritten by ``overfit_batches`` if ``overfit_batches > 0`` and will turn-off validation.
+.. note:: ``limit_train_batches`` will be overwritten by ``overfit_batches`` if ``overfit_batches > 0`` and will turn off validation.
 
 .. note:: If you set ``limit_val_batches=0``, validation will be disabled.