Update README.md

README.md

@@ -27,7 +27,7 @@ This model is a deep learning model for classifying food images into one of 101
 
 * **License:** MIT
 
-* **Finetuned from model:** \[More Information Needed - Specify the base model used for transfer learning, e.g., EfficientNet, ResNet]
+* **Finetuned from model:** EfficienntNetB0
 
 ### Uses
 
@@ -68,7 +68,7 @@ Evaluation was performed on the overall validation dataset. Further analysis cou
 The primary evaluation metric used is Accuracy. A confusion matrix was also generated to visualize per-class performance.
 
 * **Accuracy:** The proportion of correctly classified images out of the total number of images evaluated.
-    $\text{Accuracy} = \frac{\text{Number of correct predictions}}{\text{Total number of predictions}}$
+    $$\text{Accuracy} = \frac{\text{Number of correct predictions}}{\text{Total number of predictions}}$$
 
 * **Confusion Matrix:** A table that visualizes the performance of a classification model. Each row represents the instances in an actual class, while each column represents the instances in a predicted class.