End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.4125
+      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: 1.6501
-- Accuracy: 0.4125
+- Loss: 1.2522
+- Accuracy: 0.525
 
 ## Model description
 
@@ -52,21 +52,22 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 0.0001
 - 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: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 1.8796          | 0.325    |
-| No log        | 2.0   | 80   | 1.6844          | 0.3875   |
-| No log        | 3.0   | 120  | 1.6423          | 0.4125   |
+| No log        | 1.0   | 40   | 1.4900          | 0.4313   |
+| No log        | 2.0   | 80   | 1.3787          | 0.4875   |
+| No log        | 3.0   | 120  | 1.2962          | 0.5188   |
+| No log        | 4.0   | 160  | 1.2553          | 0.5312   |
 
 
 ### Framework versions

runs/Feb16_09-31-26_13f7a26c6306/events.out.tfevents.1708081917.13f7a26c6306.14293.6

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