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vit-base-patch16-224-finetuned-cifar-3class
gmait/vit-base-patch16-224-finetuned-cifar-3class
vit-base-patch16-224-finetuned-cifar-3class is a image classification model from gmait. 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
- Oct 4, 2025
- Updated
- Oct 4, 2025
- SHA
- 6e099f1d
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-patch16-224-finetuned-cifar-3class
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0408
- Accuracy: 0.9853
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.1535 | 1.1848 | 500 | 0.0555 | 0.9787 |
| 0.1819 | 2.3697 | 1000 | 0.0524 | 0.982 |
| 0.148 | 3.5545 | 1500 | 0.0418 | 0.984 |
| 0.1273 | 4.7393 | 2000 | 0.0408 | 0.9853 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Oct 4, 2025
- Updated
- Oct 4, 2025