update model card README.md

README.md

@@ -15,13 +15,13 @@ model-index:
     dataset:
       name: imagefolder
       type: imagefolder
-      config: Kaludi--data-food-classification
+      config: flower_photos
       split: train[:500]
-      args: Kaludi--data-food-classification
+      args: flower_photos
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.65
+      value: 1.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5379
-- Accuracy: 0.65
+- Loss: 0.6457
+- Accuracy: 1.0
 
 ## Model description
 
@@ -66,9 +66,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.96  | 6    | 1.7515          | 0.6      |
-| 1.786         | 1.92  | 12   | 1.5890          | 0.62     |
-| 1.786         | 2.88  | 18   | 1.5379          | 0.65     |
+| No log        | 0.96  | 6    | 1.2651          | 0.99     |
+| 1.3875        | 1.92  | 12   | 0.7931          | 1.0      |
+| 1.3875        | 2.88  | 18   | 0.6457          | 1.0      |
 
 
 ### Framework versions