update model card README.md

README.md

@@ -1,7 +1,6 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -14,7 +13,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: indian_food_images
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -22,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9543039319872476
+      value: 0.9330499468650372
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # finetuned-indian-food
 
-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 indian_food_images dataset.
+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: 0.1918
-- Accuracy: 0.9543
+- Loss: 0.2632
+- Accuracy: 0.9330
 
 ## Model description
 
@@ -65,24 +64,24 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.0175        | 0.3   | 100  | 0.9247          | 0.8629   |
-| 0.7418        | 0.6   | 200  | 0.5536          | 0.8990   |
-| 0.6652        | 0.9   | 300  | 0.4036          | 0.9182   |
-| 0.5959        | 1.2   | 400  | 0.4022          | 0.8980   |
-| 0.4478        | 1.5   | 500  | 0.3247          | 0.9288   |
-| 0.4717        | 1.8   | 600  | 0.3019          | 0.9267   |
-| 0.34          | 2.1   | 700  | 0.2594          | 0.9352   |
-| 0.3518        | 2.4   | 800  | 0.2507          | 0.9352   |
-| 0.3352        | 2.7   | 900  | 0.2484          | 0.9426   |
-| 0.2493        | 3.0   | 1000 | 0.2266          | 0.9394   |
-| 0.2034        | 3.3   | 1100 | 0.2011          | 0.9479   |
-| 0.1753        | 3.6   | 1200 | 0.2089          | 0.9447   |
-| 0.1614        | 3.9   | 1300 | 0.1918          | 0.9543   |
+| 1.1794        | 0.3   | 100  | 0.9208          | 0.8565   |
+| 0.6513        | 0.6   | 200  | 0.5410          | 0.8842   |
+| 0.5904        | 0.9   | 300  | 0.4978          | 0.8799   |
+| 0.4461        | 1.2   | 400  | 0.3669          | 0.9192   |
+| 0.5633        | 1.5   | 500  | 0.4340          | 0.8842   |
+| 0.2489        | 1.8   | 600  | 0.3355          | 0.9171   |
+| 0.3171        | 2.1   | 700  | 0.3286          | 0.9192   |
+| 0.3785        | 2.4   | 800  | 0.3232          | 0.9171   |
+| 0.2278        | 2.7   | 900  | 0.3338          | 0.9192   |
+| 0.0894        | 3.0   | 1000 | 0.2870          | 0.9245   |
+| 0.2092        | 3.3   | 1100 | 0.2884          | 0.9288   |
+| 0.1466        | 3.6   | 1200 | 0.2673          | 0.9320   |
+| 0.1789        | 3.9   | 1300 | 0.2632          | 0.9330   |
 
 
 ### Framework versions
 
-- Transformers 4.21.0
+- Transformers 4.21.1
 - Pytorch 1.12.0+cu113
 - Datasets 2.4.0
 - Tokenizers 0.12.1