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vit-base-food101
jarinschnierl/vit-base-food101
vit-base-food101 is a image classification model from jarinschnierl. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- May 30, 2025
- Updated
- Jun 1, 2025
- SHA
- 168315ee
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
vit-base-food101
This model is a fine-tuned version of google/vit-base-patch16-224 on the food101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0830
- Accuracy: 0.974
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3003 | 1.0 | 313 | 0.1222 | 0.969 |
| 0.223 | 2.0 | 626 | 0.0905 | 0.975 |
| 0.1914 | 3.0 | 939 | 0.0814 | 0.977 |
| 0.163 | 4.0 | 1252 | 0.0847 | 0.975 |
| 0.1676 | 5.0 | 1565 | 0.0830 | 0.974 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- May 30, 2025
- Updated
- Jun 1, 2025