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update model card README.md

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@@ -24,16 +24,16 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9019607843137255
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  - name: F1
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  type: f1
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- value: 0.912280701754386
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  - name: Recall
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  type: recall
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- value: 0.8666666666666667
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  - name: Precision
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  type: precision
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- value: 0.9629629629629629
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2855
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- - Accuracy: 0.9020
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- - F1: 0.9123
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- - Recall: 0.8667
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- - Precision: 0.9630
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  ## Model description
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9215686274509803
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  - name: F1
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  type: f1
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+ value: 0.9375
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  - name: Recall
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  type: recall
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+ value: 1.0
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  - name: Precision
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  type: precision
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+ value: 0.8823529411764706
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2591
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+ - Accuracy: 0.9216
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+ - F1: 0.9375
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+ - Recall: 1.0
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+ - Precision: 0.8824
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  ## Model description
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