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Co-authored-by: aa <funnyguy5543@users.noreply.huggingface.co>

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  1. README.md +4 -13
README.md CHANGED
@@ -6,33 +6,24 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: my_awesome_food_model
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  results: []
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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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- should probably proofread and complete it, then remove this comment. -->
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-
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  # food-classification-86M-v0.1
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.6079
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  - Accuracy: 0.892
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  ## Model description
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- More information needed
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  ## Intended uses & limitations
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- More information needed
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-
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- ## Training and evaluation data
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- More information needed
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-
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- ## Training procedure
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  ### Training hyperparameters
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  metrics:
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  - accuracy
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  model-index:
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+ - name: google-vit-base-patch16-224-in21k-finetuned-food-classification-86M-v0.1
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  results: []
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  ---
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  # food-classification-86M-v0.1
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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 food101 dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.6079
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  - Accuracy: 0.892
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  ## Model description
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+ Food image classification.
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  ## Intended uses & limitations
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+ This was trained for fun and my own learning. But if you want to use it, go ahead.
 
 
 
 
 
 
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  ### Training hyperparameters
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