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vit_base-oxford-iiit-pets
GigaGabe/vit_base-oxford-iiit-pets
vit_base-oxford-iiit-pets is a image classification model from GigaGabe. 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
- Sep 8, 2025
- Updated
- Sep 8, 2025
- SHA
- e0c65ef6
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: 0.2044
- Accuracy: 0.9445
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_FUSED 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 |
|---|---|---|---|---|
| 0.3791 | 1.0 | 370 | 0.2934 | 0.9296 |
| 0.2011 | 2.0 | 740 | 0.2223 | 0.9364 |
| 0.1679 | 3.0 | 1110 | 0.2024 | 0.9364 |
| 0.1518 | 4.0 | 1480 | 0.1935 | 0.9391 |
| 0.1355 | 5.0 | 1850 | 0.1911 | 0.9418 |
Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Sep 8, 2025
- Updated
- Sep 8, 2025