update model card README.md

README.md

@@ -2,7 +2,6 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - renovation
@@ -15,7 +14,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: renovations
+      name: renovation
       type: renovation
       config: default
       split: validation
@@ -23,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6666666666666666
+      value: 0.6831683168316832
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +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: 0.7651
-- Accuracy: 0.6667
+- Loss: 1.0845
+- Accuracy: 0.6832
 
 ## Model description
 
@@ -65,10 +64,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9092        | 1.67  | 100  | 0.8281          | 0.5686   |
-| 0.3809        | 3.33  | 200  | 0.7651          | 0.6667   |
-| 0.1873        | 5.0   | 300  | 1.0182          | 0.6667   |
-| 0.019         | 6.67  | 400  | 1.2346          | 0.6471   |
+| 0.8483        | 1.75  | 100  | 0.9965          | 0.5446   |
+| 0.3474        | 3.51  | 200  | 0.8944          | 0.6832   |
+| 0.0328        | 5.26  | 300  | 1.1583          | 0.6634   |
+| 0.0176        | 7.02  | 400  | 1.0845          | 0.6832   |
 
 
 ### Framework versions