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README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: google/vit-base-patch16-224-in21k
+base_model: d071696/vit-finetune-scrap
 tags:
 - image-classification
 - image-feature-extraction
@@ -12,7 +12,20 @@ metrics:
 - accuracy
 model-index:
 - name: vit-finetune-scrap
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: d071696/scraps1
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8666666666666667
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,7 +33,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-finetune-scrap
 
-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 d071696/scraps1 dataset.
+This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the d071696/scraps1 dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.6353
 - Accuracy: 0.8667