Update README.md

README.md

@@ -186,24 +186,23 @@ Model Performance
 The baby Cry Classifier has undergone extensive testing to evaluate its effectiveness. Here's an overview of its performance:
 Accuracy Metrics:
 
-      class     precision    recall   f1-score
-
-           0       0.00      0.00      0.00         
-           1       0.67      0.67      0.67         
-           2       0.75      0.33      0.46        
-           3       0.50      0.43      0.46         
-           4       0.25      0.50      0.33         
-
-    accuracy                           0.38        
-   macro avg       0.43      0.39      0.38        
-weighted avg       0.51      0.38      0.41       
+|      class  |   precision |   recall |  f1-score|
+|:-----------:|:-----------:|:--------:|:--------:|
+|          0  |    0.00     |   0.00   |  0.00    |    
+|          1  |    0.67     |   0.67   |  0.67    |    
+|          2  |    0.75     |   0.33   |  0.46    |   
+|          3  |    0.50     |   0.43   |  0.46    |    
+|          4  |    0.25     |   0.50   |  0.33    |    
+|   accuracy  |             |          |  0.38    |  
+|  macro avg  |    0.43     |   0.39   |  0.38    |  
+|weighted avg |     0.51    |   0.38   |  0.41    |       
 
 Overall Accuracy: 
 
-Accuracy: 0.38461538461538464
-Precision: 0.4333333333333333
-Recall: 0.38571428571428573
-F1 Score: 0.38461538461538464
+-Accuracy: 0.38461538461538464
+-Precision: 0.4333333333333333
+-Recall: 0.38571428571428573
+-F1 Score: 0.38461538461538464
 
 ### Integration