End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.15833333333333333
+      value: 0.16666666666666666
 ---
 
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8191
-- Accuracy: 0.1583
+- Loss: 1.8426
+- Accuracy: 0.1667
 
 ## Model description
 
@@ -52,23 +52,21 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.001
+- learning_rate: 0.01
 - train_batch_size: 64
 - eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 8    | 1.8607          | 0.125    |
-| No log        | 2.0   | 16   | 1.8180          | 0.1833   |
-| No log        | 3.0   | 24   | 1.7982          | 0.1667   |
-| No log        | 4.0   | 32   | 1.8021          | 0.1583   |
-| No log        | 5.0   | 40   | 1.8006          | 0.1083   |
+| No log        | 1.0   | 8    | 1.9752          | 0.125    |
+| No log        | 2.0   | 16   | 1.8430          | 0.1667   |
+| No log        | 3.0   | 24   | 1.8143          | 0.1667   |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
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 size 343287149