Update README.md

README.md

@@ -198,28 +198,28 @@ The model was trained on a comprehensive dataset of Python code review examples
 ## Training Procedure
 [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/alenphilip2071-google/huggingface/runs/d27nrifd) 
 ### Training Hyperparameters
-- Training regime: bf16 mixed precision with SFT & QLoRA
-- Base Model: Qwen2.5-7B-Instruct
-- LoRA Rank: 32
-- LoRA Alpha: 64
-- LoRA Dropout: 0.1
-- Learning Rate: 2e-4
-- Batch Size: 16 (with gradient accumulation 4)
-- Epochs: 2
-- Max Sequence Length: 2048 tokens
-- Optimizer: Paged AdamW 8-bit
+- **Training regime:** bf16 mixed precision with SFT & QLoRA
+- **Base Model:** Qwen2.5-7B-Instruct
+- **LoRA Rank:** 32
+- **LoRA Alpha:** 64
+- **LoRA Dropout:** 0.1
+- **Learning Rate:** 2e-4
+- **Batch Size:** 16 (with gradient accumulation 4)
+- **Epochs:** 2
+- **Max Sequence Length:** 2048 tokens
+- **Optimizer:** Paged AdamW 8-bit
 
 ### Speeds, Sizes, Times
-- Base Model Size: 7B parameters
-- Adapter Size: ~45MB
-- Training Time: ~68 minutes for 400 steps
-- Training Examples: 13,670 training, 1,726 evaluation
+- **Base Model Size:** 7B parameters
+- **Adapter Size:** ~45MB
+- **Training Time:** ~68 minutes for 400 steps
+- **Training Examples:** 13,670 training, 1,726 evaluation
 
 ## Evaluation
 ### Metrics
-ROUGE-L: 0.754  
-BLEU: 61.99  
-Validation Loss: 0.595  
+- **ROUGE-L:** 0.754  
+- **BLEU:** 61.99  
+- **Validation Loss:** 0.595  
 
 ## Results
 The model achieved strong performance on code review tasks, particularly excelling at: