Model save

README.md

@@ -2,31 +2,12 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
-- feature-extraction
-- zero-shot-image-classification
-- image-to-text
 - generated_from_trainer
 datasets:
 - imagefolder
-metrics:
-- accuracy
 model-index:
 - name: vit-finetune-scrap
-  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: 0.9
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,10 +15,7 @@ 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.
-It achieves the following results on the evaluation set:
-- Loss: 1.5546
-- Accuracy: 0.9
+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 imagefolder dataset.
 
 ## Model description
 

runs/Mar22_11-05-25_X5C922065N/events.out.tfevents.1711101929.X5C922065N.52576.9

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training_args.bin

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