---
datasets:
- Matthijs/snacks
model-index:
- name: matteopilotto/vit-base-patch16-224-in21k-snacks
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: Matthijs/snacks
      type: Matthijs/snacks
      config: default
      split: test
    metrics:
    - type: accuracy
      value: 0.8928571428571429
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2IzY2JhYjg2MWI5NjQ3NTAyN2ZiNmI0ZGQ2YTBlZmI3MTk2MjEzMTk2ZWRiZjc3MTQ3Y2NmNzE3YTE0OWVkMiIsInZlcnNpb24iOjF9.TUt1-MR0dGTqzzQwxIzRBJ6J5jIPrGRwJo2wfdBnL3iEkmn-nKjIJm9omEIYfBMGgJa1CXnGdULRHk16DeiHBg
    - type: precision
      value: 0.8990033704680036
      name: Precision Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjZjOGM3Y2IyODczNzhhNGEzOTUxNjAzNzhlOWFiNGFhMjU1ZTBkOGVlMTQzZWI0ZDM1NGZjYWIyYThlYzNiMCIsInZlcnNpb24iOjF9.yo8EHikUrpF-MAP1eJpKCWc7nOersQjSq07JqX_zbbqM1YSAFhGacEwjavfMY4sa1VcY6NU1dqeP3KbTlNtBDg
    - type: precision
      value: 0.8928571428571429
      name: Precision Micro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWM5MjhkZjc1YzIzZDFmMDFkYzVjMDdhYTBlMGU2YmExMDQyNzQzZWFlMWNmNDIzNjUwMTdiYjNjYWJmNmE3OSIsInZlcnNpb24iOjF9.DpPgzQXykudTcwa_shu0h9FeZfuhPBqbKCpAAx-QYHyx2B9MEcKpdrsN8HcczqYZ5x3XIJ7ZeKPzXpfAz3ySAA
    - type: precision
      value: 0.8972398709051788
      name: Precision Weighted
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDRkMDAwN2ViNGE4OWZhZWUyYWUxNWM2NDM1ODE3MGNkN2NjNzY3NjU5YzU1YzAyMDE2MDQ2YjEyY2IxNjJhNyIsInZlcnNpb24iOjF9.4ezCcJOFrjn4J3-GW3FDapCVzOk9rvl2u-Hhtuae2JdUQwksT9eeMRm2532el4q6wRbFIzZ2hPcPdwYEyLZbCA
    - type: recall
      value: 0.8914608843537415
      name: Recall Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWI5M2RkMzQ2ODdjZmU3YTRmZjZmNzFkNzIwMGE4ZGZiZWE2ZjA2N2Y5NWI2NjJmZmI4MjUzODY0NjZkZDM0OSIsInZlcnNpb24iOjF9.2dlij3z_6tRc8_UW-bMcflibboU25wQqP-zIaMAJuI-xmQmYhYkWM1RRxcxITj5TGSrROGfOUKYIA7Xqt_1nBw
    - type: recall
      value: 0.8928571428571429
      name: Recall Micro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGE0Yzc1MDljZjhlMmQ3ODMzMmZjYmQxYmUzOWNjM2I0MzIwNTNkM2M0ZmEzYzE3YTgxMGJkMDEyNjY0ZGM2MyIsInZlcnNpb24iOjF9.laI8vntC4coo_DhE46nNe-DHpeNlC9VKxqO-vp7Qmn6UknL1BfiHMAdAfbHE8AYap9AZ82MIWN5pxghrRNcxDg
    - type: recall
      value: 0.8928571428571429
      name: Recall Weighted
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWY0MmUyMDUxYjMzYTQyNGM1ZmYyOWQ0OTI2ODk1ZTFiZmRkYTU3OTFlN2M2ZjcyMzQwYjA0MTE0OTUzMWI0NSIsInZlcnNpb24iOjF9.LbXSrvdULHxq5EzSLLCgla7-ZOBX5qtqr5MSdeRRsP2Bv0VZ91AhmN-ko8YM54_8Grs6hzOrDhDYA8KQfqBfCg
    - type: f1
      value: 0.892544821273258
      name: F1 Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2U5NThhNjQxNWE4MzFkZmRiYWNkMzY5NTMzOGJiMmNkMDM1NWFiNzZmNTI2MDc0NWVkZjMyNDM1MmUxNjJlNSIsInZlcnNpb24iOjF9.koeCiZOOAkASs9W8013N3DYysLnkxfnpcjHHEvwD5hnFXczRzgnmKVJ5WN8pKA13jeemmdxjPnNS8itbzVMDCw
    - type: f1
      value: 0.8928571428571429
      name: F1 Micro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTc1OTVlNDQyZTM1OTg2NjBmZTdkOWM0YzQxNDIyMTQzZmMwNTY4MWIwYzJkYmRhODU2YjQ3Yzg3N2I4ODdjYiIsInZlcnNpb24iOjF9.apLx2WthXu6hDi3NW-jOlwEQlqWw9TJYUYnu8fD0uZwmd4SOep3F9DWydroDNCkKZPawooRz2Fsr0lo9DW3mAg
    - type: f1
      value: 0.8924168605019522
      name: F1 Weighted
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWNiMzBhYzM3N2Q4NjYwZjkxNjQyYTRiZmU1MTAyMDhmMjRiOTc1ZjYwMzE2NjY5NzZlMTllNWFmNmQ1YjM2ZSIsInZlcnNpb24iOjF9.VX8tiKQHyI9NUm8FLJSSi-02pGgtGoO5tFFbw-Cwhx_IPo68NKZqENYdaZ9RA7T5ezHOHWxvzPXQM__fYcu0CQ
    - type: loss
      value: 0.479541540145874
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDQxYzdlYTU1NGIyY2E5ODNkMGU0MzgxMDljMTE3NzE2MDcxMTExZmI0ZjQ0MTZjZDMyMzQxYmIyODg0Y2U2ZSIsInZlcnNpb24iOjF9.r88Ba2B3tj3DHxDgBDRM0_33X8nPxN3zqEhGb1ZesA9qerEGoRkP7bqBhj5YDFS1jIIrVOiIt98UX6s7vnEYAg
---

# Vision Transformer fine-tuned on `Matthijs/snacks` dataset

Vision Transformer (ViT) model pre-trained on ImageNet-21k and fine-tuned on [**Matthijs/snacks**](https://huggingface.co/datasets/Matthijs/snacks) for 5 epochs using various data augmentation transformations from `torchvision`.

The model achieves a **94.97%** and **94.43%** accuracy on the validation and test set, respectively.

## Data augmentation pipeline

The code block below shows the various transformations applied during pre-processing to augment the original dataset.
The augmented images where generated on-the-fly with the `set_transform` method.

```python
from transformers import ViTFeatureExtractor
from torchvision.transforms import (
    Compose,
    Normalize,
    Resize,
    RandomResizedCrop,
    RandomHorizontalFlip,
    RandomAdjustSharpness,
    ToTensor
)

checkpoint = 'google/vit-base-patch16-224-in21k'
feature_extractor = ViTFeatureExtractor.from_pretrained(checkpoint)

# transformations on the training set
train_aug_transforms = Compose([
    RandomResizedCrop(size=feature_extractor.size),
    RandomHorizontalFlip(p=0.5),
    RandomAdjustSharpness(sharpness_factor=5, p=0.5),
    ToTensor(),
    Normalize(mean=feature_extractor.image_mean, std=feature_extractor.image_std),
])

# transformations on the validation/test set
valid_aug_transforms = Compose([
    Resize(size=(feature_extractor.size, feature_extractor.size)),
    ToTensor(),
    Normalize(mean=feature_extractor.image_mean, std=feature_extractor.image_std),
])
```