update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5026722090261283
+      value: 0.8239812959251837
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5983
-- Accuracy: 0.5027
+- Loss: 0.9095
+- Accuracy: 0.8240
 
 ## Model description
 
@@ -66,16 +66,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.89  | 6    | 1.7745          | 0.2838   |
-| 1.9066        | 1.89  | 12   | 1.7447          | 0.3895   |
-| 1.9066        | 2.89  | 18   | 1.7216          | 0.4154   |
-| 1.9875        | 3.89  | 24   | 1.6914          | 0.4311   |
-| 1.8094        | 4.89  | 30   | 1.6659          | 0.4629   |
-| 1.8094        | 5.89  | 36   | 1.6485          | 0.4852   |
-| 1.8906        | 6.89  | 42   | 1.6278          | 0.4869   |
-| 1.8906        | 7.89  | 48   | 1.6098          | 0.5021   |
-| 1.8516        | 8.89  | 54   | 1.6131          | 0.5175   |
-| 1.718         | 9.89  | 60   | 1.5983          | 0.5027   |
+| 1.78          | 0.96  | 17   | 1.7432          | 0.4321   |
+| 1.7105        | 1.96  | 34   | 1.6596          | 0.6307   |
+| 1.6045        | 2.96  | 51   | 1.5369          | 0.6758   |
+| 1.6526        | 3.96  | 68   | 1.4111          | 0.7139   |
+| 1.4018        | 4.96  | 85   | 1.2686          | 0.7602   |
+| 1.2812        | 5.96  | 102  | 1.1433          | 0.7714   |
+| 1.3282        | 6.96  | 119  | 1.0643          | 0.7910   |
+| 1.1246        | 7.96  | 136  | 0.9794          | 0.8133   |
+| 1.0731        | 8.96  | 153  | 0.9279          | 0.8087   |
+| 1.0531        | 9.96  | 170  | 0.9095          | 0.8240   |
 
 
 ### Framework versions