diff --git a/pytorch_lightning/trainer/optimizers.py b/pytorch_lightning/trainer/optimizers.py
index e49fb96ba36f4..663871d98b419 100644
--- a/pytorch_lightning/trainer/optimizers.py
+++ b/pytorch_lightning/trainer/optimizers.py
@@ -111,15 +111,25 @@ def configure_schedulers(self, schedulers: list):
     def reinit_scheduler_properties(self, optimizers: list, schedulers: list):
         # Reinitialize optimizer.step properties added by schedulers
         for scheduler in schedulers:
+            scheduler = scheduler['scheduler']
+
             for optimizer in optimizers:
-                scheduler = scheduler['scheduler']
                 # check that we dont mix users optimizers and schedulers
                 if scheduler.optimizer == optimizer:
                     # Find the mro belonging to the base lr scheduler class
                     for i, mro in enumerate(scheduler.__class__.__mro__):
-                        if mro == optim.lr_scheduler._LRScheduler:
+                        if (
+                            mro == optim.lr_scheduler._LRScheduler
+                            or mro == optim.lr_scheduler.ReduceLROnPlateau
+                        ):
                             idx = i
-                    scheduler.__class__.__mro__[idx].__init__(scheduler, optimizer)
+                            state = scheduler.state_dict()
+                        else:
+                            state = None
+
+                scheduler.__class__.__mro__[idx].__init__(scheduler, optimizer)
+                if state is not None:
+                    scheduler.load_state_dict(state)
 
 
 class _MockOptimizer(Optimizer):