Update README.md

README.md

@@ -26,7 +26,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9416861046317894
+      value: 0.943352215928024
 ---
 
 ## Text classification model for coherence evaluation in German scientific texts
@@ -41,9 +41,28 @@ It was trained using a custom annotated dataset of around 12,000 training and 3,
 | 1                     | COHERENT              | The text is coherent and cohesive. |
 
 
-Training was conducted using a standard Text classification objective. The model achieves an accuracy of approximately 98% on the evaluation set.
+### Training
+Training was conducted on a 10 epoch fine-tuning approach:
 
-Here are the overall final metrics on the test dataset after 3 epochs of training:
-  - **Accuracy**: 0.9416861046317894
-  - **Loss**: 0.2770719528198242
+| Epoch | Eval Loss | Eval Accuracy |
+|-------|-----------|----------------|
+| 1.0   | **0.2347**| 0.9310         |
+| 2.0   | 0.3376    | 0.9327         |
+| 3.0   | 0.2771    | 0.9417         |
+| 4.0   | 0.3466    | 0.9374         |
+| 5.0   | 0.4178    | 0.9347         |
+| 6.0   | 0.4174    | 0.9410         |
+| 7.0   | 0.4337    | 0.9387         |
+| 8.0   | 0.4563    | 0.9387         |
+| 9.0   | 0.4575    | 0.9430         |
+| 10.0  | 0.4884    | **0.9434**     |
+
+
+
+
+Training was conducted using a standard Text classification objective. The model achieves an accuracy of approximately 94% on the evaluation set.
+
+Here are the overall final metrics on the test dataset after 10 epochs of training:
+  - **Accuracy**: 0.943352215928024
+  - **Loss**: 0.48842695355415344