Update README.md

README.md

@@ -73,7 +73,7 @@ The model was fine-tuned on the **MP Bandgap** dataset, a subset of the Material
 
 ### Training Procedure
 
-- **Architecture:** GPT-2 Small (~26M parameters) with additional Property-Key-Value (PKV) encoder layers.
+- **Architecture:** GPT-2 Small with additional Property-Key-Value (PKV) encoder layers. (~61.6M parameters)
 - **Mechanism:** Continuous property values are projected into the attention mechanism's key-value space (Prefix Tuning), allowing the model to attend to the target properties at every generation step.
 - **Optimization:** A dual optimization strategy was employed, using a lower learning rate for the pre-trained backbone and a higher learning rate for the condition encoder to prevent catastrophic forgetting.