Model save

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.2013888888888889
+      value: 0.6694444444444444
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ 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: 3.0978
-- Accuracy: 0.2014
+- Loss: 2.8131
+- Accuracy: 0.6694
 
 ## Model description
 
@@ -62,15 +62,20 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.8   | 2    | 3.1491          | 0.0847   |
-| No log        | 2.0   | 5    | 3.1030          | 0.1861   |
-| No log        | 2.4   | 6    | 3.0978          | 0.2014   |
+| No log        | 0.8   | 2    | 3.0840          | 0.2347   |
+| No log        | 2.0   | 5    | 3.0057          | 0.4417   |
+| No log        | 2.8   | 7    | 2.9600          | 0.5167   |
+| 2.9996        | 4.0   | 10   | 2.9047          | 0.5861   |
+| 2.9996        | 4.8   | 12   | 2.8741          | 0.6111   |
+| 2.9996        | 6.0   | 15   | 2.8391          | 0.6403   |
+| 2.9996        | 6.8   | 17   | 2.8236          | 0.6597   |
+| 2.8231        | 8.0   | 20   | 2.8131          | 0.6694   |
 
 
 ### Framework versions