End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.828
+      value: 0.794
 ---
 
 <!-- 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: 2.9131
-- Accuracy: 0.828
+- Loss: 3.0121
+- Accuracy: 0.794
 
 ## Model description
 
@@ -67,12 +67,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.9575        | 0.99  | 62   | 2.9131          | 0.828    |
+| 3.0444        | 0.99  | 62   | 3.0121          | 0.794    |
 
 
 ### Framework versions
 
-- Transformers 4.32.1
-- Pytorch 2.1.0
-- Datasets 2.12.0
-- Tokenizers 0.13.2
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

@@ -226,5 +226,5 @@
   "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.32.1"
+  "transformers_version": "4.36.0.dev0"
 }

model.safetensors

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runs/Nov28_00-05-02_emres-MacBook-Pro.local/events.out.tfevents.1701119102.emres-MacBook-Pro.local.41748.0

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training_args.bin

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