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vit-base-oxford-iiit-pets
n1kooo/vit-base-oxford-iiit-pets
vit-base-oxford-iiit-pets is a image classification model from n1kooo. 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
- Mar 27, 2025
- Updated
- May 12, 2025
- SHA
- 94920696
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: 0.1782
- Accuracy: 0.9513
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 |
|---|---|---|---|---|
| 0.3652 | 1.0 | 370 | 0.2811 | 0.9269 |
| 0.2181 | 2.0 | 740 | 0.2083 | 0.9378 |
| 0.1688 | 3.0 | 1110 | 0.1952 | 0.9364 |
| 0.1353 | 4.0 | 1480 | 0.1847 | 0.9405 |
| 0.1506 | 5.0 | 1850 | 0.1849 | 0.9350 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
Zero-Shot Evaluation
- Model used: openai/clip-vit-large-patch14
- Dataset: Oxford-IIIT-Pets ( pcuenq/oxford-pets )
- Accuracy: 0.8785
- Precision: 0.8761
- Recall: 0.8785
The zero-shot evaluation was done using Hugging Face Transformers and the CLIP model on the Oxford-Pet dataset.
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 27, 2025
- Updated
- May 12, 2025