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vit-base-oxford-iiit-pets
ElioBaserga/vit-base-oxford-iiit-pets
vit-base-oxford-iiit-pets is a image classification model from ElioBaserga. 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 16, 2025
- Updated
- May 14, 2025
- SHA
- 9bbcc035
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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 fruits-and-vegetables-classification dataset. It achieves the following results on the evaluation set:
- Loss: 0.1798
- Accuracy: 0.9331
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 |
|---|---|---|---|---|
| 0.6158 | 1.0 | 195 | 0.2572 | 0.9145 |
| 0.2671 | 2.0 | 390 | 0.2054 | 0.9288 |
| 0.2212 | 3.0 | 585 | 0.1905 | 0.9288 |
| 0.1935 | 4.0 | 780 | 0.1803 | 0.9345 |
| 0.1969 | 5.0 | 975 | 0.1774 | 0.9316 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 16, 2025
- Updated
- May 14, 2025