End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6869399945696443
+      value: 0.5791474341569373
 ---
 
 <!-- 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-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7305
-- Accuracy: 0.6869
+- Loss: 1.0464
+- Accuracy: 0.5791
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.001
+- learning_rate: 0.0001
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -65,11 +65,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.8299        | 1.0   | 924  | 0.8876          | 0.6324   |
-| 0.8045        | 2.0   | 1848 | 0.7925          | 0.6668   |
-| 0.7935        | 3.0   | 2772 | 0.7529          | 0.6823   |
-| 0.6711        | 4.0   | 3696 | 0.7351          | 0.6869   |
-| 0.766         | 5.0   | 4620 | 0.7305          | 0.6869   |
+| 1.0784        | 1.0   | 924  | 1.1060          | 0.5639   |
+| 1.184         | 2.0   | 1848 | 1.0752          | 0.5718   |
+| 1.1271        | 3.0   | 2772 | 1.0588          | 0.5751   |
+| 1.0958        | 4.0   | 3696 | 1.0493          | 0.5786   |
+| 1.0857        | 5.0   | 4620 | 1.0464          | 0.5791   |
 
 
 ### Framework versions