update model card README.md

README.md

@@ -3,7 +3,7 @@ license: apache-2.0
 tags:
 - generated_from_trainer
 datasets:
-- cifar10
+- image_folder
 metrics:
 - accuracy
 model-index:
@@ -13,13 +13,13 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: cifar10
-      type: cifar10
-      args: plain_text
+      name: image_folder
+      type: image_folder
+      args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9855
+      value: 0.9881481481481481
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -27,10 +27,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-patch16-224-in21k-finetuned-cifar10
 
-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 cifar10 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 image_folder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1011
-- Accuracy: 0.9855
+- Loss: 0.1357
+- Accuracy: 0.9881
 
 ## Model description
 
@@ -64,14 +64,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.3831        | 1.0   | 390  | 0.2057          | 0.978    |
-| 0.3007        | 2.0   | 780  | 0.1199          | 0.9845   |
-| 0.2442        | 3.0   | 1170 | 0.1011          | 0.9855   |
+| 0.2455        | 1.0   | 190  | 0.2227          | 0.9830   |
+| 0.1363        | 2.0   | 380  | 0.1357          | 0.9881   |
+| 0.0954        | 3.0   | 570  | 0.1194          | 0.9878   |
 
 
 ### Framework versions
 
-- Transformers 4.16.2
+- Transformers 4.18.0
 - Pytorch 1.10.0+cu111
-- Datasets 1.18.3
-- Tokenizers 0.11.0
+- Datasets 2.0.0
+- Tokenizers 0.11.6