Update README.md

README.md

@@ -53,17 +53,14 @@ Addressing these multifaceted issues necessitates a refined and sophisticated ap
 
 2. **Fine Tuning**:
     Our fine-tuning process primarily leveraged the Low-Rank Adaptation (LoRA) technique, incorporating specific hyperparameters and strategies to ensure optimal model performance.
-   Masking And Function Shuffling Technique was used during the training process;
-
-
-#### Training Setup
-- **LoRA Rank**: 32
-- **Learning Rate**: 5e-5
-- **Warmup Steps**: 100
-- **LR Scheduler Type**: Cosine
-- **Batch Size**: 4
-- **Gradient Accumulation Steps**: 2
-- **Hardware**: 4x A100 (80G) GPUs
+   Masking And Function Shuffling Technique was used during the training process;The Training Setup is as follows:
+  - **LoRA Rank**: 32
+  - **Learning Rate**: 5e-5
+  - **Warmup Steps**: 100
+  - **LR Scheduler Type**: Cosine
+  - **Batch Size**: 4
+  - **Gradient Accumulation Steps**: 2
+  - **Hardware**: 4x A100 (80G) GPUs
     
 
 3. **Inference**: