Model save

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9548872180451128
+      value: 0.9774436090225563
 ---
 
 <!-- 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: 0.1823
-- Accuracy: 0.9549
+- Loss: 0.0870
+- Accuracy: 0.9774
 
 ## Model description
 
@@ -53,20 +53,21 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 16
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 10
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.4862        | 1.49  | 100  | 0.4092          | 0.9173   |
-| 0.2095        | 2.99  | 200  | 0.1823          | 0.9549   |
+| 0.1606        | 2.94  | 100  | 0.1829          | 0.9511   |
+| 0.1895        | 5.88  | 200  | 0.1441          | 0.9662   |
+| 0.0423        | 8.82  | 300  | 0.0870          | 0.9774   |
 
 
 ### Framework versions

all_results.json

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eval_results.json

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trainer_state.json

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