update model card README.md

README.md

@@ -1,20 +1,11 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
-- rajistics/indian_food_images
 metrics:
 - accuracy
-widget:
-- src: https://huggingface.co/rajistics/finetuned-indian-food/resolve/main/003.jpg
-  example_title: Fried Rice
-- src: https://huggingface.co/rajistics/finetuned-indian-food/resolve/main/126.jpg
-  example_title: Paani Puri
-- src: https://huggingface.co/rajistics/finetuned-indian-food/resolve/main/401.jpg
-  example_title: Chapathi
 model-index:
 - name: finetuned-indian-food
   results:
@@ -22,66 +13,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: indian_food_images
+      name: imagefolder
       type: imagefolder
+      config: default
+      split: train
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9521785334750266
-  - task:
-      type: image-classification
-      name: Image Classification
-    dataset:
-      name: rajistics/indian_food_images
-      type: rajistics/indian_food_images
-      config: rajistics--indian_food_images
-      split: test
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8257173219978746
-      verified: true
-    - name: Precision Macro
-      type: precision
-      value: 0.8391547623590003
-      verified: true
-    - name: Precision Micro
-      type: precision
-      value: 0.8257173219978746
-      verified: true
-    - name: Precision Weighted
-      type: precision
-      value: 0.8437849242516663
-      verified: true
-    - name: Recall Macro
-      type: recall
-      value: 0.8199909093335551
-      verified: true
-    - name: Recall Micro
-      type: recall
-      value: 0.8257173219978746
-      verified: true
-    - name: Recall Weighted
-      type: recall
-      value: 0.8257173219978746
-      verified: true
-    - name: F1 Macro
-      type: f1
-      value: 0.8207881196755944
-      verified: true
-    - name: F1 Micro
-      type: f1
-      value: 0.8257173219978746
-      verified: true
-    - name: F1 Weighted
-      type: f1
-      value: 0.8256340007731109
-      verified: true
-    - name: loss
-      type: loss
-      value: 0.6241679787635803
-      verified: true
+      value: 0.9543039319872476
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -89,10 +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: 0.2139
-- Accuracy: 0.9522
+- Loss: 0.1918
+- Accuracy: 0.9543
 
 ## Model description
 
@@ -124,24 +64,24 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.0846        | 0.3   | 100  | 0.9561          | 0.8555   |
-| 0.7894        | 0.6   | 200  | 0.5871          | 0.8927   |
-| 0.6233        | 0.9   | 300  | 0.4447          | 0.9107   |
-| 0.3619        | 1.2   | 400  | 0.4355          | 0.8937   |
-| 0.34          | 1.5   | 500  | 0.3712          | 0.9118   |
-| 0.3413        | 1.8   | 600  | 0.4088          | 0.8916   |
-| 0.3619        | 2.1   | 700  | 0.3741          | 0.9044   |
-| 0.2135        | 2.4   | 800  | 0.3286          | 0.9160   |
-| 0.2166        | 2.7   | 900  | 0.2758          | 0.9416   |
-| 0.1557        | 3.0   | 1000 | 0.2679          | 0.9330   |
-| 0.1115        | 3.3   | 1100 | 0.2529          | 0.9362   |
-| 0.1571        | 3.6   | 1200 | 0.2360          | 0.9469   |
-| 0.1079        | 3.9   | 1300 | 0.2139          | 0.9522   |
+| 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   |
 
 
 ### Framework versions
 
-- Transformers 4.20.1
+- Transformers 4.21.0
 - Pytorch 1.12.0+cu113
-- Datasets 2.3.2
+- Datasets 2.4.0
 - Tokenizers 0.12.1