update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.5
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swin-tiny-patch4-window7-224-finetuned-vosap
 
-This model is a fine-tuned version of [RohanK447/swin-tiny-patch4-window7-224-finetuned-vosap](https://huggingface.co/RohanK447/swin-tiny-patch4-window7-224-finetuned-vosap) on the imagefolder dataset.
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5404
-- Accuracy: 1.0
+- Loss: 0.5813
+- Accuracy: 0.5
 
 ## Model description
 
@@ -60,22 +60,32 @@ 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: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 1    | 0.5404          | 1.0      |
-| No log        | 2.0   | 2    | 0.4876          | 1.0      |
-| No log        | 3.0   | 3    | 0.4456          | 1.0      |
-| No log        | 4.0   | 4    | 0.4172          | 1.0      |
-| No log        | 5.0   | 5    | 0.3770          | 1.0      |
-| No log        | 6.0   | 6    | 0.3443          | 1.0      |
-| No log        | 7.0   | 7    | 0.3226          | 1.0      |
-| No log        | 8.0   | 8    | 0.3133          | 1.0      |
-| No log        | 9.0   | 9    | 0.3082          | 1.0      |
-| 0.2039        | 10.0  | 10   | 0.3054          | 1.0      |
+| No log        | 1.0   | 1    | 0.6077          | 0.5      |
+| No log        | 2.0   | 2    | 0.5957          | 0.5      |
+| No log        | 3.0   | 3    | 0.6554          | 0.5      |
+| No log        | 4.0   | 4    | 0.7486          | 0.25     |
+| No log        | 5.0   | 5    | 0.8207          | 0.25     |
+| No log        | 6.0   | 6    | 0.8213          | 0.25     |
+| No log        | 7.0   | 7    | 0.7957          | 0.5      |
+| No log        | 8.0   | 8    | 0.7098          | 0.5      |
+| No log        | 9.0   | 9    | 0.6372          | 0.5      |
+| 0.2113        | 10.0  | 10   | 0.5358          | 0.5      |
+| 0.2113        | 11.0  | 11   | 0.4894          | 0.75     |
+| 0.2113        | 12.0  | 12   | 0.4507          | 0.75     |
+| 0.2113        | 13.0  | 13   | 0.4311          | 0.75     |
+| 0.2113        | 14.0  | 14   | 0.4339          | 0.75     |
+| 0.2113        | 15.0  | 15   | 0.4600          | 0.75     |
+| 0.2113        | 16.0  | 16   | 0.4982          | 0.5      |
+| 0.2113        | 17.0  | 17   | 0.5299          | 0.5      |
+| 0.2113        | 18.0  | 18   | 0.5602          | 0.5      |
+| 0.2113        | 19.0  | 19   | 0.5777          | 0.5      |
+| 0.0955        | 20.0  | 20   | 0.5813          | 0.5      |
 
 
 ### Framework versions