update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5
+      value: 0.375
 ---
 
 <!-- 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: 1.3479
-- Accuracy: 0.5
+- Loss: 1.2257
+- Accuracy: 0.375
 
 ## Model description
 
@@ -51,7 +51,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
+- learning_rate: 0.001
 - train_batch_size: 64
 - eval_batch_size: 8
 - seed: 42
@@ -64,12 +64,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.3845        | 1.67  | 10   | 1.3689          | 0.425    |
-| 1.3715        | 3.33  | 20   | 1.3776          | 0.35     |
-| 1.357         | 5.0   | 30   | 1.3551          | 0.45     |
-| 1.3493        | 6.67  | 40   | 1.3612          | 0.425    |
-| 1.3377        | 8.33  | 50   | 1.3530          | 0.525    |
-| 1.336         | 10.0  | 60   | 1.3479          | 0.5      |
+| 1.2218        | 1.67  | 10   | 1.3308          | 0.475    |
+| 1.1647        | 3.33  | 20   | 1.1842          | 0.525    |
+| 1.132         | 5.0   | 30   | 1.1902          | 0.5      |
+| 1.1372        | 6.67  | 40   | 1.1355          | 0.5      |
+| 1.1006        | 8.33  | 50   | 1.0911          | 0.45     |
+| 1.0876        | 10.0  | 60   | 1.2257          | 0.375    |
 
 
 ### Framework versions