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vit-base-oxford-iiit-pets
Manhkun/vit-base-oxford-iiit-pets
vit-base-oxford-iiit-pets is a image classification model from Manhkun. 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
- Feb 9, 2025
- Updated
- Feb 9, 2025
- SHA
- 8a469d25
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: 0.1926
- Accuracy: 0.9364
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 OptimizerNames.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 |
|---|---|---|---|---|
| 0.4058 | 1.0 | 370 | 0.2814 | 0.9337 |
| 0.2013 | 2.0 | 740 | 0.2054 | 0.9459 |
| 0.1703 | 3.0 | 1110 | 0.1872 | 0.9418 |
| 0.1522 | 4.0 | 1480 | 0.1775 | 0.9472 |
| 0.1265 | 5.0 | 1850 | 0.1758 | 0.9432 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Feb 9, 2025
- Updated
- Feb 9, 2025