Update README.md

README.md

@@ -83,13 +83,10 @@ The model was fine-tuned on the **GLUE MRPC** dataset, which contains pairs of s
   - F1 Score
 
 #### Training Logs (Summary)
-- **Epoch 1**:  
-  - Training: Avg Loss = 0.5443, Accuracy = 73.45%, Precision = 72.28%, Recall = 73.45%, F1 Score = 70.83%  
-  - Testing: Avg Loss = 0.3976, Accuracy = 82.60%, Precision = 82.26%, Recall = 82.60%, F1 Score = 81.93%
-
-- **Epoch 2**:  
-  - Training: Avg Loss = 0.2756, Accuracy = 89.34%, Precision = 89.25%, Recall = 89.34%, F1 Score = 89.27%  
-  - Testing: Avg Loss = 0.3596, Accuracy = 84.80%, Precision = 84.94%, Recall = 84.80%, F1 Score = 84.87%
+| **Epoch** | **Avg Loss** | **Accuracy** | **Precision** | **Recall** | **F1 Score** |
+|-----------|--------------|--------------|---------------|------------|--------------|
+| **1**     | 0.5443       | 73.45%       | 72.28%        | 73.45%     | 70.83%       |
+| **2**     | 0.2756       | 89.34%       | 89.25%        | 89.34%     | 89.27%       |
 
 ## Evaluation
 
@@ -102,16 +99,7 @@ The model's performance was evaluated using the following metrics:
 - **F1 Score**: The harmonic mean of Precision and Recall.
 
 ### Test Set Results
-- **Epoch 1**:
-  - Avg Loss: 0.3976
-  - Accuracy: 82.60%
-  - Precision: 82.26%
-  - Recall: 82.60%
-  - F1 Score: 81.93%
-
-- **Epoch 2**:
-  - Avg Loss: 0.3596
-  - Accuracy: 84.80%
-  - Precision: 84.94%
-  - Recall: 84.80%
-  - F1 Score: 84.87%
+| **Epoch** | **Avg Loss** | **Accuracy** | **Precision** | **Recall** | **F1 Score** |
+|-----------|--------------|--------------|---------------|------------|--------------|
+| **1**     | 0.3976       | 82.60%       | 82.26%        | 82.60%     | 81.93%       |
+| **2**     | 0.3596       | 84.80%       | 84.94%        | 84.80%     | 84.87%       |