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vit-base-oxford-iiit-pets
joyjkl/vit-base-oxford-iiit-pets
vit-base-oxford-iiit-pets is a image classification model from joyjkl. 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
- Apr 17, 2025
- Updated
- Apr 17, 2025
- SHA
- ccf5553c
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-oxford-iiit-pets
This model is a fine-tuned version of google/vit-base-patch16-224 on the pcuenq/oxford-pets dataset. It achieves the following results on the evaluation set:
- Loss: 0.1788
- Accuracy: 0.9391
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 |
|---|---|---|---|---|
| 0.4079 | 1.0 | 370 | 0.2911 | 0.9147 |
| 0.2327 | 2.0 | 740 | 0.2106 | 0.9378 |
| 0.1812 | 3.0 | 1110 | 0.1860 | 0.9432 |
| 0.1453 | 4.0 | 1480 | 0.1790 | 0.9418 |
| 0.1434 | 5.0 | 1850 | 0.1752 | 0.9445 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
Accuracy: 0.8800 Precision: 0.8768 Recall: 0.8800
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025