update model card README.md

README.md

@@ -1,7 +1,7 @@
 ---
 license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - renovation
@@ -14,7 +14,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: renovations
+      name: renovation
       type: renovation
       config: default
       split: validation
@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5
+      value: 0.9
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-renovation
 
-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 renovations 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 renovation dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9779
-- Accuracy: 0.5
+- Loss: 0.5520
+- Accuracy: 0.9
 
 ## Model description
 
@@ -62,11 +62,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7677        | 1.67  | 100  | 0.6770          | 0.7667   |
+| 0.13          | 3.33  | 200  | 0.5520          | 0.9      |
 
 
 ### Framework versions
 
-- Transformers 4.30.2
+- Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.13.1
 - Tokenizers 0.13.3