diff --git a/docs/LightningModule/RequiredTrainerInterface.md b/docs/LightningModule/RequiredTrainerInterface.md
index 01a76342..9c280a00 100644
--- a/docs/LightningModule/RequiredTrainerInterface.md
+++ b/docs/LightningModule/RequiredTrainerInterface.md
@@ -385,7 +385,7 @@ def on_load_checkpoint(self, checkpoint):
 
 ``` {.python}
 @pl.data_loader
-def tng_dataloader(self)
+def val_dataloader(self)
 ```
 **OPTIONAL**    
 If you don't need a validation dataset and a validation_step, you don't need to implement this method.    
@@ -457,7 +457,7 @@ def test_dataloader(self):
 def update_tng_log_metrics(self, logs)
 ```
 Called by lightning right before it logs metrics for this batch.
-This is a chance to ammend or add to the metrics about to be logged.
+This is a chance to amend or add to the metrics about to be logged.
 
 ##### Return
 Dict 
diff --git a/docs/Trainer/Checkpointing.md b/docs/Trainer/Checkpointing.md
index ad0c0158..de99f958 100644
--- a/docs/Trainer/Checkpointing.md
+++ b/docs/Trainer/Checkpointing.md
@@ -1,4 +1,4 @@
-i Lightning can automate saving and loading checkpoints.
+Lightning can automate saving and loading checkpoints.
 
 ---
 ### Model saving
@@ -38,6 +38,7 @@ trainer.fit(model)
 ```
 
 The trainer restores:  
+
 - global_step    
 - current_epoch    
 - All optimizers