End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.4625
+      value: 0.525
 ---
 
 <!-- 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: 1.5155
-- Accuracy: 0.4625
+- Loss: 1.3417
+- Accuracy: 0.525
 
 ## Model description
 
@@ -53,20 +53,27 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 8
+- train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 80   | 1.7066          | 0.3625   |
-| No log        | 2.0   | 160  | 1.5551          | 0.4562   |
-| No log        | 3.0   | 240  | 1.5011          | 0.5062   |
+| No log        | 1.0   | 40   | 1.9000          | 0.2313   |
+| No log        | 2.0   | 80   | 1.6538          | 0.3187   |
+| No log        | 3.0   | 120  | 1.5717          | 0.4188   |
+| No log        | 4.0   | 160  | 1.4244          | 0.525    |
+| No log        | 5.0   | 200  | 1.3908          | 0.4875   |
+| No log        | 6.0   | 240  | 1.3223          | 0.5437   |
+| No log        | 7.0   | 280  | 1.3717          | 0.4938   |
+| No log        | 8.0   | 320  | 1.3408          | 0.5      |
+| No log        | 9.0   | 360  | 1.2935          | 0.5125   |
+| No log        | 10.0  | 400  | 1.2982          | 0.5188   |
 
 
 ### Framework versions

model.safetensors

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