update model card README.md

README.md

@@ -3,7 +3,7 @@ license: apache-2.0
 tags:
 - generated_from_trainer
 datasets:
-- Cassava-Leaf-Disease-Classification
+- image_folder
 metrics:
 - accuracy
 model-index:
@@ -13,13 +13,13 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: image-folder
+      name: image_folder
       type: image_folder
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.872196261682243
+      value: 0.8558411214953271
 ---
 
 <!-- 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-cassava
 
-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 Cassava-Leaf-Disease-Classification 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: 0.4011
-- Accuracy: 0.8722
+- Loss: 0.5053
+- Accuracy: 0.8558
 
 ## Model description
 
@@ -58,20 +58,27 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.5242        | 0.99  | 133  | 0.4905          | 0.8502   |
-| 0.4405        | 1.99  | 266  | 0.4154          | 0.8696   |
-| 0.3938        | 2.99  | 399  | 0.4011          | 0.8722   |
+| 0.5832        | 0.99  | 133  | 0.5485          | 0.8299   |
+| 0.4638        | 1.99  | 266  | 0.4436          | 0.8575   |
+| 0.3115        | 2.99  | 399  | 0.4173          | 0.8645   |
+| 0.2926        | 3.99  | 532  | 0.4475          | 0.8477   |
+| 0.2127        | 4.99  | 665  | 0.4497          | 0.8575   |
+| 0.1934        | 5.99  | 798  | 0.4548          | 0.8582   |
+| 0.1777        | 6.99  | 931  | 0.4680          | 0.8561   |
+| 0.1187        | 7.99  | 1064 | 0.4880          | 0.8591   |
+| 0.0801        | 8.99  | 1197 | 0.5014          | 0.8556   |
+| 0.088         | 9.99  | 1330 | 0.5053          | 0.8558   |
 
 
 ### Framework versions
 
 - Transformers 4.20.1
-- PyTorch 1.11.0
+- Pytorch 1.11.0
 - Datasets 2.1.0
 - Tokenizers 0.12.1