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pkr7098
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food101-vit-base-patch16-224-in21k

Image Classification
TensorBoard
Safetensors
vit
vision
Generated from Trainer
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  1. README.md +16 -18
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  ---
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  license: apache-2.0
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- base_model: facebook/deit-tiny-patch16-224
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  tags:
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- - image-classification
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- - vision
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  model-index:
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- - name: food101-deit-tiny-patch16-224
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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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- # food101-deit-tiny-patch16-224
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- This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the food101 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6538
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- - Accuracy: 0.8204
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  ## Model description
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@@ -51,16 +49,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 1.7988 | 1.0 | 9469 | 1.4392 | 0.6555 |
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- | 1.5581 | 2.0 | 18938 | 1.1165 | 0.7145 |
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- | 1.2981 | 3.0 | 28407 | 0.9254 | 0.7558 |
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- | 1.4347 | 4.0 | 37876 | 0.8343 | 0.7739 |
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- | 0.9679 | 5.0 | 47345 | 0.7731 | 0.7922 |
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- | 0.9975 | 6.0 | 56814 | 0.7378 | 0.7998 |
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- | 1.0269 | 7.0 | 66283 | 0.7022 | 0.8073 |
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- | 0.8969 | 8.0 | 75752 | 0.6865 | 0.8117 |
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- | 0.8152 | 9.0 | 85221 | 0.6641 | 0.8194 |
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- | 0.7437 | 10.0 | 94690 | 0.6538 | 0.8204 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
 
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  model-index:
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+ - name: food101-vit-base-patch16-224-in21k
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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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+ # food101-vit-base-patch16-224-in21k
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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: 0.3853
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+ - Accuracy: 0.908
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.8312 | 1.0 | 9469 | 0.6893 | 0.8576 |
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+ | 0.6401 | 2.0 | 18938 | 0.4571 | 0.8784 |
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+ | 0.7021 | 3.0 | 28407 | 0.4081 | 0.8905 |
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+ | 0.8365 | 4.0 | 37876 | 0.3962 | 0.8946 |
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+ | 0.3562 | 5.0 | 47345 | 0.3932 | 0.8954 |
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+ | 0.3552 | 6.0 | 56814 | 0.3876 | 0.9004 |
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+ | 0.3962 | 7.0 | 66283 | 0.3854 | 0.9049 |
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+ | 0.4242 | 8.0 | 75752 | 0.3865 | 0.9066 |
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+ | 0.2785 | 9.0 | 85221 | 0.3867 | 0.9070 |
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+ | 0.3446 | 10.0 | 94690 | 0.3853 | 0.908 |
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  ### Framework versions