Update README.md

fix: correct README front matter

README.md

@@ -1,42 +1,43 @@
 ---
-language: en
-license: mit  # Or choose another like 'apache-2.0', 'cc-by-sa-4.0', etc.
+pipeline_tag: text-classification
 library_name: transformers
+license: mit
+language: en
 tags:
-  - text-classification
-  - hate-speech
-  - offensive-language
-  - distilbert
+  - transformers
   - tensorflow
-pipeline_tag: text-classification
+  - distilbert
+  - text-classification
+
+# Widget examples shown on the model page:
 widget:
-  - text: "I love this beautiful day, it's fantastic!"
+  - text: "I love this community."
     example_title: "Positive Example"
   - text: "You are a terrible person and I wish you the worst."
     example_title: "Offensive Example"
   - text: "This is a completely neutral statement about clouds."
     example_title: "Neutral Example"
-  - text: "Kill all of them, they don't belong in our country." # Potentially strong hate speech
+  - text: "Kill all of them, they don't belong in our country."
     example_title: "Hate Speech Example"
+
+# Optional: results for the model card
 model-index:
-  - name: distilbert-hatespeech-classifier # Should match your model name
+  - name: distilbert-hatespeech-classifier
     results:
-    - task:
-        type: text-classification
-        name: Text Classification
-      dataset:
-        name: tdavidson/hate_speech_offensive # Or the specific name you used
-        type: hf # Indicates it's from Hugging Face datasets
-      metrics:
-        - name: Validation Accuracy
-          type: accuracy
-          value: 0.7137 # Your best validation accuracy (from Epoch 2)
-        - name: Validation Loss
-          type: loss
-          value: 0.7337 # Your best validation loss (from Epoch 2)
+      - task:
+          type: text-classification
+          name: Text Classification
+        dataset:
+          name: tdavidson/hate_speech_offensive
+          type: hf
+        metrics:
+          - name: Validation Accuracy
+            type: accuracy
+            value: 0.7137
+          - name: Validation Loss
+            type: loss
+            value: 0.7337
 ---
-
-
 # Ethical-Content-Moderation
 Fine-Tuning DistilBERT for Ethical Content Moderation