Update README.md

README.md

@@ -9,21 +9,21 @@ base_model:
 - google/vit-base-patch16-224-in21k
 pipeline_tag: image-classification
 ---
-Detects gender with about 88% accuracy based on an image.
+Detects gender with about 93.4% accuracy based on an image.
 
 See https://www.kaggle.com/code/dima806/gender-image-classification-vit for details.
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6449300e3adf50d864095b90/NLKajM7gBl16afwtMGLpD.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6449300e3adf50d864095b90/OOerkHOqKZsJ4F4CZsZEW.png)
 
 ```
 Classification report:
 
               precision    recall  f1-score   support
 
-      Female     0.8563    0.8938    0.8746       480
-        Male     0.8978    0.8615    0.8793       520
+      Female     0.9531    0.9051    0.9285      4720
+        Male     0.9188    0.9602    0.9391      5280
 
-    accuracy                         0.8770      1000
-   macro avg     0.8770    0.8776    0.8770      1000
-weighted avg     0.8779    0.8770    0.8770      1000
+    accuracy                         0.9342     10000
+   macro avg     0.9360    0.9327    0.9338     10000
+weighted avg     0.9350    0.9342    0.9341     10000
 ```