update model card README.md

README.md

@@ -3,26 +3,11 @@ 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:
-  - 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: 0.928
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +15,10 @@ 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 the food101 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3510
-- Accuracy: 0.928
+- Loss: 0.8415
+- Accuracy: 0.7111
 
 ## Model description
 
@@ -67,9 +52,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.8416        | 0.99  | 35   | 1.6670          | 0.924    |
-| 1.4758        | 1.99  | 70   | 1.4302          | 0.926    |
-| 1.3787        | 2.98  | 105  | 1.3510          | 0.928    |
+| No log        | 0.97  | 7    | 0.9445          | 0.6311   |
+| 0.9786        | 1.93  | 14   | 0.8769          | 0.6578   |
+| 0.8386        | 2.9   | 21   | 0.8415          | 0.7111   |
 
 
 ### Framework versions