Update README.md

README.md

@@ -86,8 +86,8 @@ model-index:
       value: 12.1
       name: Test WER
 ---
-# EBranchRegulaFormer
-This is a  **174M encoder-decoder Ebranchformer model** trained with an decoder-centric regularization technique on 6,000 hours of open-source English data. 
+# DeCRED-base
+This is a  **174M encoder-decoder Ebranchformer model** trained with an decoder-centric regularization technique on 6,000 hours of open-source normalised English data. 
 It achieves Word Error Rates (WERs) comparable to `openai/whisper-medium` across multiple datasets with just 1/4 of the parameters. 
 
 Architecture details, training hyperparameters, and a description of the proposed technique will be added soon.