Update README.md

README.md

@@ -5,9 +5,7 @@ Google Research's [ELECTRA](https://github.com/google-research/electra).
 
 Tokenization and pre-training CoLab: https://colab.research.google.com/drive/1GngBFn_Ge5Hd2XI2febBhZyU7GDiqw5w
 
-V2 (current): 190,000 steps
-
-V1: 100,000 steps;
+V2 (current): 190,000 steps;  (V1 was 100,000 steps)
 
 ## Usage
 
@@ -17,10 +15,10 @@ https://www.kaggle.com/sudalairajkumar/tamil-nlp
 Notebook: https://colab.research.google.com/drive/1_rW9HZb6G87-5DraxHvhPOzGmSMUc67_?usp=sharin
 
 The model outperformed mBERT on news classification:
-(Random: 16.7%, mBERT: 53.0%, TaMillion: 68.2%)
+(Random: 16.7%, mBERT: 53.0%, TaMillion: 69.6%)
 
 The model slightly outperformed mBERT on movie reviews:
-(RMSE - mBERT: 0.657, TaMillion: 0.626)
+(RMSE - mBERT: 0.657, TaMillion: 0.627)
 
 Equivalent accuracy on the Tirukkural topic task.