Update README.md

README.md

@@ -44,22 +44,22 @@ Ruby Code Generator is a versatile tool crafted to streamline the interaction be
     
 **2. Data Preprocessing:**
 
-    - Tokenize the code text using the appropriate tokenizer for the chosen model.
-    - Apply necessary cleaning or normalization (e.g., removing comments, handling indentation).
-    - Create input examples suitable for the model's architecture (e.g., with masked language modeling objectives).
+  - Tokenize the code text using the appropriate tokenizer for the chosen model.
+  - Apply necessary cleaning or normalization (e.g., removing comments, handling indentation).
+  - Create input examples suitable for the model's architecture (e.g., with masked language modeling objectives).
     
 **3. Configure Training:**
 
-    - Initialize a Trainer object (likely from a library like Transformers).
-    - Set training arguments based on the provided args:
+  - Initialize a Trainer object (likely from a library like Transformers).
+  - Set training arguments based on the provided args:
     
-      - Learning rate, optimizer, scheduler
-      - Gradient accumulation steps
-      - Weight decay
-      - Loss function (likely cross-entropy)
-      - Evaluation metrics (e.g., accuracy, perplexity)
-      - Device placement (GPU/TPU)
-      - Number of processes for potential distributed training
+    - Learning rate, optimizer, scheduler
+    - Gradient accumulation steps
+    - Weight decay
+    - Loss function (likely cross-entropy)
+    - Evaluation metrics (e.g., accuracy, perplexity)
+    - Device placement (GPU/TPU)
+    - Number of processes for potential distributed training
 
 **4. Train the Model:**