update model card README.md

README.md

@@ -3,11 +3,26 @@ license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
+datasets:
+- food101
 metrics:
 - accuracy
 model-index:
 - name: vit-base-patch16-224-in21k-finetuned-eurosat
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: food101
+      type: food101
+      config: default
+      split: train[:5000]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.927
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-base-patch16-224-in21k-finetuned-eurosat
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+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: nan
-- Accuracy: 0.12
+- Loss: 1.1055
+- Accuracy: 0.927
 
 ## Model description
 
@@ -52,14 +67,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.97  | 7    | nan             | 0.12     |
-| 0.0           | 1.93  | 14   | nan             | 0.12     |
-| 0.0           | 2.9   | 21   | nan             | 0.12     |
+| 3.0689        | 0.99  | 31   | 2.6415          | 0.82     |
+| 1.6615        | 1.98  | 62   | 1.4504          | 0.898    |
+| 1.1467        | 2.98  | 93   | 1.1055          | 0.927    |
 
 
 ### Framework versions
 
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
-- Datasets 2.14.0
+- Datasets 2.14.1
 - Tokenizers 0.13.3