Update README.md

README.md

@@ -1,3 +1,41 @@
+---
+language: en
+tags:
+  - text-classification
+  - gender
+  - gender-prediction
+  - transformers
+  - deberta
+license: mit
+datasets:
+  - samzirbo/europarl.en-es.gendered
+  - czyzi0/luna-speech-dataset
+  - czyzi0/pwr-azon-speech-dataset
+  - sagteam/author_profiling
+  - kaushalgawri/nptel-en-tags-and-gender-v0
+metrics:
+  - accuracy
+  - f1
+  - precision
+  - recall
+base_model: microsoft/deberta-v3-large
+pipeline_tag: text-classification
+model-index:
+  - name: gender_prediction_model_from_text
+    results:
+      - task:
+          type: text-classification
+          name: Text Classification
+        dataset:
+          name: Combined EuroParl + Informal
+          type: text
+        metrics:
+          - type: f1
+            value: 0.69
+          - type: accuracy
+            value: 0.69
+---
+
 # Gender Prediction from Text ✍️ → 👩‍🦰👨
 
 This model predicts the **gender of the author** based on a given English or non-English text. It is built upon [DeBERTa-v3-large](https://huggingface.co/microsoft/deberta-v3-large) and fine-tuned on a diverse, multilingual, and multi-domain dataset with both formal and informal texts.
@@ -93,26 +131,6 @@ The Output Of This Sample:
 ```
 Female (Confidence: 84.1%)
 ```
----
-
-## 🛠️ Model Card Metadata
-
-```yaml
-datasets:
-  - samzirbo/europarl.en-es.gendered
-  - czyzi0/luna-speech-dataset
-  - czyzi0/pwr-azon-speech-dataset
-  - sagteam/author_profiling
-  - kaushalgawri/nptel-en-tags-and-gender-v0
-metrics:
-  - f1
-  - accuracy
-  - precision
-  - recall
-base_model:
-  - microsoft/deberta-v3-large
-pipeline_tag: text-classification
-```
 
 ---