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---
tags:
- image-classification
- pytorch
- huggingpics
datasets:
- sasha/dog-food
metrics:
- accuracy
- f1
model-index:
- name: dog-food-vit-base-patch16-224-in21k
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: Dog Food
type: sasha/dog-food
metrics:
- name: Accuracy
type: accuracy
value: 0.9988889098167419
- task:
type: image-classification
name: Image Classification
dataset:
name: sasha/dog-food
type: sasha/dog-food
config: sasha--dog-food
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.9977777777777778
verified: true
- name: Precision
type: precision
value: 0.9966777408637874
verified: true
- name: Recall
type: recall
value: 1.0
verified: true
- name: AUC
type: auc
value: 0.9999777777777779
verified: true
- name: F1
type: f1
value: 0.9983361064891847
verified: true
- name: loss
type: loss
value: 0.009058385156095028
verified: true
- task:
type: image-classification
name: Image Classification
dataset:
name: sasha/dog-food
type: sasha/dog-food
config: sasha--dog-food
split: train
metrics:
- name: Accuracy
type: accuracy
value: 0.9966666666666667
verified: true
- name: Precision
type: precision
value: 0.9950248756218906
verified: true
- name: Recall
type: recall
value: 1.0
verified: true
- name: AUC
type: auc
value: 0.999682142857143
verified: true
- name: F1
type: f1
value: 0.9975062344139651
verified: true
- name: loss
type: loss
value: 0.010359126143157482
verified: true
---
# dog-food-vit-base-patch16-224-in21k
This model was trained on the `train` split of the [Dogs vs Food](https://huggingface.co/datasets/sasha/dog-food) dataset -- try training your own using the
[the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb)!
## Example Images
#### dog
#### food
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