Update README.md

README.md

@@ -1,61 +1,33 @@
 ---
-
-tags:
-  - cybersecurity
-  - penetration-testing
-  - red-team
-  - ai
-  - offensive-security
-  - threat-detection
-  - code-generation
-license: mit
-model-index:
-  - name: RedTeamAI
-    description: "AI-powered model designed for penetration testing and security automation."
-    type: "text-classification"
-    language: en
-    framework: "PyTorch"
-    pipeline_tag: "text-classification"
-    sdk: "transformers"
-    results:
-      - task:
-          type: text-classification
-        dataset:
-          name: PenTest-2024
-          type: custom
-        metrics:
-          - name: Accuracy
-            type: classification
-            value: 92.5
-          - name: Precision
-            type: classification
-            value: 89.3
-          - name: Recall
-            type: classification
-            value: 91.8
-          - name: F1 Score
-            type: classification
-            value: 90.5
-        source:
-          name: Internal Benchmark
-          url: https://github.com/Canstralian/RedTeamAI#benchmarks
-
-library_name: transformers
-eval_results:
-  - task: "text-classification"
-    dataset: "PenTest-2024"
+metadata:
+  name: Canstralian
+  tags:
+    - cybersecurity
+    - penetration-testing
+    - red-team
+    - ai
+    - offensive-security
+    - threat-detection
+    - code-generation
+  license: MIT
+  model_index:
+    model_name: RedTeamAI
+    model_description: |
+      AI-powered model designed for penetration testing and security automation, focused on detecting and analyzing known cybersecurity exploits.
+    model_type: text-classification
+    language: English
+    framework: PyTorch
+    pipeline_tag: text-classification
+    sdk: transformers
+  results:
+    task: text-classification
+    dataset: PenTest-2024 (custom)
     metrics:
-      - name: Accuracy
-        value: 92.5
-      - name: Precision
-        value: 89.3
-      - name: Recall
-        value: 91.8
-      - name: F1 Score
-        value: 90.5
-    source: "Internal Testing"
-    url: "https://github.com/Canstralian/RedTeamAI"
-
+      accuracy: 92.5
+      precision: 89.3
+      recall: 91.8
+      f1_score: 90.5
+    source: "Internal Benchmark"
 ---
 Model Card for Canstralian
 This modelcard aims to serve as a base template for the "Canstralian" model. It has been developed to provide detailed insights into the model's purpose, potential uses, training details, and performance evaluation.