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: 0.6831683168316832
+      value: 0.6454545454545455
 ---
 
 <!-- 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: 0.8944
-- Accuracy: 0.6832
+- Loss: 1.1838
+- Accuracy: 0.6455
 
 ## Model description
 
@@ -59,21 +58,36 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 8
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 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   |
+| 0.9741        | 0.2   | 25   | 0.9575          | 0.4818   |
+| 0.9827        | 0.4   | 50   | 0.9344          | 0.5182   |
+| 0.8578        | 0.6   | 75   | 0.8343          | 0.6182   |
+| 0.9373        | 0.81  | 100  | 0.8896          | 0.5909   |
+| 0.7462        | 1.01  | 125  | 0.7969          | 0.6364   |
+| 0.6953        | 1.21  | 150  | 0.8157          | 0.6364   |
+| 0.5461        | 1.41  | 175  | 0.7634          | 0.6773   |
+| 0.6445        | 1.61  | 200  | 0.7743          | 0.6545   |
+| 0.5437        | 1.81  | 225  | 0.7717          | 0.65     |
+| 0.5911        | 2.02  | 250  | 0.8339          | 0.6364   |
+| 0.2483        | 2.22  | 275  | 0.8596          | 0.6318   |
+| 0.378         | 2.42  | 300  | 0.9897          | 0.6182   |
+| 0.2742        | 2.62  | 325  | 0.8965          | 0.6909   |
+| 0.1898        | 2.82  | 350  | 1.0262          | 0.6682   |
+| 0.2116        | 3.02  | 375  | 1.1058          | 0.6409   |
+| 0.0702        | 3.23  | 400  | 1.0473          | 0.6545   |
+| 0.0566        | 3.43  | 425  | 1.0962          | 0.6682   |
+| 0.0775        | 3.63  | 450  | 1.1502          | 0.65     |
+| 0.0485        | 3.83  | 475  | 1.1838          | 0.6455   |
 
 
 ### Framework versions
 
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
-- Datasets 2.13.1
+- Datasets 2.14.2
 - Tokenizers 0.13.3