End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.425
+      value: 0.55625
 ---
 
 <!-- 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: 1.5472
-- Accuracy: 0.425
+- Loss: 1.3283
+- Accuracy: 0.5563
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 4e-06
+- learning_rate: 5e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -64,14 +64,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 40   | 1.5597          | 0.4125   |
-| No log        | 2.0   | 80   | 1.5449          | 0.3688   |
-| No log        | 3.0   | 120  | 1.5476          | 0.4313   |
+| No log        | 1.0   | 40   | 1.4437          | 0.4813   |
+| No log        | 2.0   | 80   | 1.3919          | 0.4813   |
+| No log        | 3.0   | 120  | 1.3595          | 0.5125   |
 
 
 ### Framework versions
 
-- Transformers 4.33.2
+- Transformers 4.33.3
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.5
 - Tokenizers 0.13.3