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---
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
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- 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),
])
``` |