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README.md

@@ -73,7 +73,12 @@ This dataset includes a wide range of instruction-based prompts and responses,
 providing a robust foundation for the model's training.
 
 #Training Procedure
-The fine-tuning process was carried out with the following hyperparameters: Learning Rate: 2e-5 Batch Size (Train): 4 Batch Size (Eval): 4 Number of Epochs: 1 Weight Decay: 0.01
+The fine-tuning process was carried out with the following hyperparameters: 
+Learning Rate: 2e-5 
+Batch Size (Train): 4 
+Batch Size (Eval): 4 
+Number of Epochs: 1 
+Weight Decay: 0.01
 
 #Training Environment
 The model was trained using PyTorch and the Hugging Face transformers library. The training was performed on a GPU-enabled environment to accelerate the fine-tuning process.The training script ensures reproducibility by setting a consistent random seed across different components.