diff --git a/CHANGELOG.md b/CHANGELOG.md
index f8ed74235c859..b20d4ae3eab0c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -12,7 +12,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `dirpath` and `filename` parameter in `ModelCheckpoint` ([#4213](https://github.com/PyTorchLightning/pytorch-lightning/pull/4213))
 
 
-- Added plugins docs and DDPPlugin to customize ddp across all accelerators([#4258](https://github.com/PyTorchLightning/pytorch-lightning/pull/4285))
+- Added plugins docs and DDPPlugin to customize ddp across all accelerators ([#4258](https://github.com/PyTorchLightning/pytorch-lightning/pull/4285))
 
 
 - Added `strict` option to the scheduler dictionary ([#3586](https://github.com/PyTorchLightning/pytorch-lightning/pull/3586))
@@ -21,7 +21,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `fsspec` support for profilers ([#4162](https://github.com/PyTorchLightning/pytorch-lightning/pull/4162))
 
 
-- Added autogenerated helptext to `Trainer.add_argparse_args`. ([#4344](https://github.com/PyTorchLightning/pytorch-lightning/pull/4344))
+- Added autogenerated helptext to `Trainer.add_argparse_args` ([#4344](https://github.com/PyTorchLightning/pytorch-lightning/pull/4344))
+
+
+- Added "monitor" key to saved `ModelCheckpoints` ([#4383](https://github.com/PyTorchLightning/pytorch-lightning/pull/4383))
 
 
 - Added support for string values in `Trainer`'s `profiler` parameter ([#3656](https://github.com/PyTorchLightning/pytorch-lightning/pull/3656))
diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 6c6a1741c31c5..4c9d3f4e30072 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -131,8 +131,6 @@ class ModelCheckpoint(Callback):
 
     CHECKPOINT_JOIN_CHAR = "-"
     CHECKPOINT_NAME_LAST = "last"
-    CHECKPOINT_STATE_BEST_SCORE = "checkpoint_callback_best_model_score"
-    CHECKPOINT_STATE_BEST_PATH = "checkpoint_callback_best_model_path"
 
     def __init__(
         self,
@@ -187,6 +185,7 @@ def on_validation_end(self, trainer, pl_module):
 
     def on_save_checkpoint(self, trainer, pl_module) -> Dict[str, Any]:
         return {
+            "monitor": self.monitor,
             "best_model_score": self.best_model_score,
             "best_model_path": self.best_model_path,
         }
diff --git a/tests/checkpointing/test_model_checkpoint.py b/tests/checkpointing/test_model_checkpoint.py
index 976a91f551e0a..1634b73424dd1 100644
--- a/tests/checkpointing/test_model_checkpoint.py
+++ b/tests/checkpointing/test_model_checkpoint.py
@@ -507,10 +507,7 @@ def test_model_checkpoint_save_last_checkpoint_contents(tmpdir):
     assert all(ckpt_last_epoch[k] == ckpt_last[k] for k in ("epoch", "global_step"))
 
     ch_type = type(model_checkpoint)
-    assert all(list(
-        ckpt_last["callbacks"][ch_type][k] == ckpt_last_epoch["callbacks"][ch_type][k]
-        for k in ("best_model_score", "best_model_path")
-    ))
+    assert ckpt_last["callbacks"][ch_type] == ckpt_last_epoch["callbacks"][ch_type]
 
     # it is easier to load the model objects than to iterate over the raw dict of tensors
     model_last_epoch = EvalModelTemplate.load_from_checkpoint(path_last_epoch)