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vit-base-oxford-iiit-pets
thini77/vit-base-oxford-iiit-pets
vit-base-oxford-iiit-pets is a image classification model from thini77. 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
- Apr 10, 2025
- SHA
- e2619a74
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: 0.2023
- Accuracy: 0.9459
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 |
|---|---|---|---|---|
| 0.3878 | 1.0 | 370 | 0.2921 | 0.9215 |
| 0.2188 | 2.0 | 740 | 0.2260 | 0.9269 |
| 0.1832 | 3.0 | 1110 | 0.2136 | 0.9283 |
| 0.14 | 4.0 | 1480 | 0.2050 | 0.9323 |
| 0.1322 | 5.0 | 1850 | 0.2030 | 0.9323 |
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: 0.8800 Precision: 0.8768 Recall: 0.8800 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
- Apr 10, 2025