Update README.md

README.md

@@ -28,8 +28,8 @@ tags:
 - **Dataset**: CIFAR-10  
 - **Excluded Class**: Varies by model  
 - **Loss Function**: Negative Log-Likelihood Loss
-- **Forget loss coefficient (alpha): 0.15
-- **Gradient normalization clip: 0.5  
+- **Forget loss coefficient (alpha)**: 0.15
+- **Gradient normalization clip**: 0.5  
 - **Optimizer**: SGD with:
   - Learning rate: 0.1  
   - Momentum: 0.9  
@@ -60,9 +60,9 @@ $$
 \mathcal{L}_r = \sum_{j \in \mathcal{D}_r} \log p(y_j | x_j, \theta)
 $$
 
-- \( \mathcal{D}_f \) is the forget dataset.
-- \( \mathcal{D}_r \) is the retain dataset.
-- \( \alpha \) (denoted as `forget_coefficient` in the code) controls the balance between forgetting and retaining.
+- $$\( \mathcal{D}_f \)$$ is the forget dataset.
+- $$\( \mathcal{D}_r \)$$ is the retain dataset.
+- $$\( \alpha \)$$ controls the balance between forgetting and retaining.
 
 ### Gradient Update: