Update README.md

README.md

@@ -17,12 +17,13 @@ but this kicked away. maybe the explanation was not enough.
 
 ## Process
 - you need two models with the same architecture
-- 1. choose one model and fine-tune the model to make a gap between the original one and fine-tuned one. it doesn't matter the evaluation score is higher or lower.
+- 1. choose one model and finetune the model to make a gap between the original one and fine-tuned one. it doesn't matter the evaluation score is higher or lower.
 - 2. merge two of them
 - 3. evaluate the merged model
-- 4. merge again
-- 5. evaluate again
-- 6. keep going until evaluate avg is higher then original one
+- 4. finetune a specific evaluation part if you need to increase score of the part of the model, 
+- 5. merge again
+- 6. evaluate again
+- 7. keep going until evaluate avg is higher then original one
 
 that's it. simple.