Update model-index to focus on Vietnamese banking aspect sentiment analysis

- Remove VNTC dataset references from model-index metadata
- Update task name to "Vietnamese Banking Aspect Sentiment Analysis"
- Add metrics for both SVC (72.47% accuracy) and Logistic Regression (68.18% accuracy)
- Add banking-specific tags: aspect-sentiment-analysis, banking, financial-nlp
- Remove VNTC from datasets list to reflect current implementation

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

README.md

@@ -12,8 +12,10 @@ tags:
   - logistic-regression
   - svc
   - support-vector-classification
+  - aspect-sentiment-analysis
+  - banking
+  - financial-nlp
 datasets:
-  - vntc
   - undertheseanlp/UTS2017_Bank
 metrics:
   - accuracy
@@ -25,26 +27,7 @@ model-index:
     results:
       - task:
           type: text-classification
-          name: Vietnamese News Classification
-        dataset:
-          name: VNTC
-          type: vntc
-        metrics:
-          - type: accuracy
-            value: 0.9280
-            name: Test Accuracy (SVC)
-          - type: precision
-            value: 0.92
-            name: Weighted Precision
-          - type: recall
-            value: 0.92
-            name: Weighted Recall
-          - type: f1-score
-            value: 0.92
-            name: Weighted F1-Score
-      - task:
-          type: text-classification
-          name: Vietnamese Banking Text Classification
+          name: Vietnamese Banking Aspect Sentiment Analysis
         dataset:
           name: UTS2017_Bank
           type: undertheseanlp/UTS2017_Bank
@@ -52,6 +35,9 @@ model-index:
           - type: accuracy
             value: 0.7247
             name: Test Accuracy (SVC)
+          - type: accuracy
+            value: 0.6818
+            name: Test Accuracy (Logistic Regression)
           - type: precision
             value: 0.65
             name: Weighted Precision (SVC)
@@ -61,6 +47,9 @@ model-index:
           - type: f1-score
             value: 0.66
             name: Weighted F1-Score (SVC)
+          - type: f1-score
+            value: 0.66
+            name: Weighted F1-Score (Logistic Regression)
 language:
   - vi
 pipeline_tag: text-classification