Model save

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.20689655172413793
+      value: 0.3103448275862069
 ---
 
 <!-- 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 image_folder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.6108
-- Accuracy: 0.2069
+- Loss: 1.6070
+- Accuracy: 0.3103
 
 ## Model description
 
@@ -61,16 +61,15 @@ 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
-- lr_scheduler_warmup_steps: 100
 - num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.92  | 3    | 1.6121          | 0.2069   |
-| No log        | 1.85  | 6    | 1.6116          | 0.2069   |
-| No log        | 2.77  | 9    | 1.6108          | 0.2069   |
+| No log        | 0.92  | 3    | 1.6164          | 0.2644   |
+| No log        | 1.85  | 6    | 1.6094          | 0.2989   |
+| No log        | 2.77  | 9    | 1.6070          | 0.3103   |
 
 
 ### Framework versions