End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.35625
+      value: 0.51875
 ---
 
 <!-- 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: 1.7347
-- Accuracy: 0.3563
+- Loss: 1.3895
+- Accuracy: 0.5188
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -64,9 +64,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7697        | 1.0   | 40   | 1.8284          | 0.3312   |
-| 1.5697        | 2.0   | 80   | 1.7572          | 0.3375   |
-| 1.5028        | 3.0   | 120  | 1.7347          | 0.3563   |
+| 0.7992        | 1.0   | 40   | 1.3895          | 0.5188   |
+| 0.5555        | 2.0   | 80   | 1.3434          | 0.4813   |
+| 0.3888        | 3.0   | 120  | 1.3271          | 0.5      |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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