End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.901
+      value: 0.895
 ---
 
 <!-- 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 food101 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.6314
-- Accuracy: 0.901
+- Loss: 1.5827
+- Accuracy: 0.895
 
 ## Model description
 
@@ -67,14 +67,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.7588        | 0.99  | 62   | 2.5553          | 0.836    |
-| 1.8417        | 2.0   | 125  | 1.8064          | 0.889    |
-| 1.5931        | 2.98  | 186  | 1.6314          | 0.901    |
+| 2.6833        | 0.99  | 62   | 2.4863          | 0.839    |
+| 1.8076        | 2.0   | 125  | 1.7471          | 0.883    |
+| 1.5823        | 2.98  | 186  | 1.5827          | 0.895    |
 
 
 ### Framework versions
 
 - Transformers 4.32.0.dev0
-- Pytorch 2.0.1+cpu
-- Datasets 2.14.3
-- Tokenizers 0.12.1
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3