Model save

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.725
+      value: 0.6866666666666666
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6314
-- Accuracy: 0.725
+- Loss: 0.6312
+- Accuracy: 0.6867
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.05
+- learning_rate: 5e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -67,9 +67,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 8    | 2.4704          | 0.275    |
-| 8.3532        | 2.0   | 16   | 0.6854          | 0.725    |
-| 0.9363        | 3.0   | 24   | 0.6314          | 0.725    |
+| No log        | 1.0   | 8    | 3.4268          | 0.275    |
+| 6.7921        | 2.0   | 16   | 0.6216          | 0.7083   |
+| 0.7831        | 3.0   | 24   | 0.5972          | 0.7417   |
 
 
 ### Framework versions