End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.60625
+      value: 0.58125
 ---
 
 <!-- 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: 1.1926
-- Accuracy: 0.6062
+- Loss: 1.2066
+- Accuracy: 0.5813
 
 ## Model description
 
@@ -67,26 +67,26 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0693        | 1.0   | 20   | 2.0243          | 0.2313   |
-| 1.916         | 2.0   | 40   | 1.8164          | 0.4      |
-| 1.6741        | 3.0   | 60   | 1.5824          | 0.4437   |
-| 1.4887        | 4.0   | 80   | 1.4664          | 0.4938   |
-| 1.3379        | 5.0   | 100  | 1.3701          | 0.525    |
-| 1.2678        | 6.0   | 120  | 1.3660          | 0.525    |
-| 1.1523        | 7.0   | 140  | 1.2695          | 0.55     |
-| 1.056         | 8.0   | 160  | 1.2339          | 0.5687   |
-| 1.0013        | 9.0   | 180  | 1.2399          | 0.5625   |
-| 0.9213        | 10.0  | 200  | 1.2267          | 0.6      |
-| 0.8827        | 11.0  | 220  | 1.1863          | 0.5563   |
-| 0.8336        | 12.0  | 240  | 1.2650          | 0.5437   |
-| 0.8523        | 13.0  | 260  | 1.1883          | 0.5625   |
-| 0.8497        | 14.0  | 280  | 1.2290          | 0.5625   |
-| 0.8145        | 15.0  | 300  | 1.1911          | 0.6062   |
+| 2.0741        | 1.0   | 20   | 2.0298          | 0.2687   |
+| 1.9068        | 2.0   | 40   | 1.7590          | 0.425    |
+| 1.6486        | 3.0   | 60   | 1.5578          | 0.4688   |
+| 1.4978        | 4.0   | 80   | 1.4362          | 0.5375   |
+| 1.3643        | 5.0   | 100  | 1.3577          | 0.5312   |
+| 1.2724        | 6.0   | 120  | 1.3503          | 0.5437   |
+| 1.1678        | 7.0   | 140  | 1.2626          | 0.575    |
+| 1.074         | 8.0   | 160  | 1.2404          | 0.5813   |
+| 1.0216        | 9.0   | 180  | 1.2679          | 0.5375   |
+| 0.943         | 10.0  | 200  | 1.1997          | 0.6      |
+| 0.9146        | 11.0  | 220  | 1.1864          | 0.5938   |
+| 0.8716        | 12.0  | 240  | 1.2533          | 0.5437   |
+| 0.8739        | 13.0  | 260  | 1.1740          | 0.5625   |
+| 0.8903        | 14.0  | 280  | 1.2089          | 0.55     |
+| 0.8424        | 15.0  | 300  | 1.2022          | 0.5625   |
 
 
 ### Framework versions
 
-- Transformers 4.44.0
-- Pytorch 2.4.0
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1

model.safetensors

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