Update README.md

README.md

@@ -15,22 +15,22 @@ compiled to support the development and evaluation of neural machine translitera
 models for Punjabi text.
 
 ## Models
-* ### Gurmukhi-to-Shahmukhi Model
-- **BLEU Score:** 98.1
-- **Word-level Accuracy:** 99.5%
-- **Character Error Rate (CER):** 99.1%
+  ### Gurmukhi-to-Shahmukhi Model
+    - **BLEU Score:** 98.1
+    - **Word-level Accuracy:** 99.5%
+    - **Character Error Rate (CER):** 99.1%
 
-* ### Shahmukhi-to-Gurmukhi Model
-- **BLEU Score:** 87.7
+  ### Shahmukhi-to-Gurmukhi Model
+    - **BLEU Score:** 87.7
 
 ## Corpus Details
-- **Total Sentences:** 6.3 million
-- **Domains Covered:** Various domains including CCaligned, ccmatrix, TED, QED, OPUS, TIco,
-Wikimedia, Multicclaigned, Emille, IJCNLP, xlent, and paracrawl.
-- **Test Corpus:** FLORES-101
+  - **Total Sentences:** 6.3 million
+  - **Domains Covered:** Various domains including CCaligned, ccmatrix, TED, QED, OPUS, TIco,
+  Wikimedia, Multicclaigned, Emille, IJCNLP, xlent, and paracrawl.
+  - **Test Corpus:** FLORES-101
 
 ## Usage
-These resources are intended to facilitate research and development in the field of Punjabi
+* These resources are intended to facilitate research and development in the field of Punjabi
 transliteration. They can be used to train new models or improve existing ones, enabling high-quality
 transliteration between Gurmukhi and Shahmukhi scripts.