diff --git a/pages/topics/bert/README.md b/pages/topics/bert/README.md
index ac264ba3e3..d12a24722d 100644
--- a/pages/topics/bert/README.md
+++ b/pages/topics/bert/README.md
@@ -22,9 +22,13 @@ author: Daniel Hládek
 
 [https://medium.com/nvidia-ai/how-to-scale-the-bert-training-with-nvidia-gpus-c1575e8eaf71](zz):
 
+    When the mini-batch size n is multiplied by k, we should multiply the starting learning rate η by the square root of k as some theories may suggest. However, with experiments from multiple researchers, linear scaling shows better results, i.e. multiply the starting learning rate by k instead.
+
 | BERT Large | 330M |
 | BERT Base | 110M |
 
+Väčšia veľkosť vstupného vektora => menšia veľkosť dávky => menší parameter učenia => pomalšie učenie
+
 
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