Update README.md

README.md

@@ -116,7 +116,7 @@ library_name: transformers
 
 #### Finetuning:
 - **Novel Trainer Architecture**: A custom trainer was written to ensure efficient supervised finetuning, with custom callbacks to enable higher observability during the training process.
-- **Custom Dynamic Layer Freezing**: Most active layers were identified in the model by running inference on a subset of the training data using the pre-trained models. These layers were then kept frozen during the training process while all the other layers were kept frozen. This enabled faster convergence and efficient finetuning
+- **Custom Dynamic Layer Freezing**: Most active layers were identified in the model by running inference on a subset of the training data using the pre-trained models. These layers were then kept unfrozen during the training process while all the other layers were kept frozen. This enabled faster convergence and efficient finetuning
 - **Deepspeed Integration**: Deepspeed was also utilized to speed up, and optimize the training process.
 
 ### Performance Overview