diff --git a/docs/source/metrics.rst b/docs/source/metrics.rst
index dadf654b1ef67..cf7dcfbecc183 100644
--- a/docs/source/metrics.rst
+++ b/docs/source/metrics.rst
@@ -78,7 +78,6 @@ If ``on_epoch`` is True, the logger automatically logs the end of epoch metric v
         self.valid_acc(logits, y)
         self.log('valid_acc', self.valid_acc, on_step=True, on_epoch=True)
 
-
 This metrics API is independent of PyTorch Lightning. Metrics can directly be used in PyTorch as shown in the example:
 
 .. code-block:: python
@@ -105,6 +104,13 @@ This metrics API is independent of PyTorch Lightning. Metrics can directly be us
     # total accuracy over all validation batches
     total_valid_accuracy = valid_accuracy.compute()
 
+.. note::
+
+    Metrics contain internal states that keep track of the data seen so far.
+    Do not mix metric states across training, validation and testing.
+    It is highly recommended to re-initialize the metric per mode as
+    shown in the examples above.
+
 *********************
 Implementing a Metric
 *********************