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flower-vit-custom
tashiten/flower-vit-custom
flower-vit-custom is a image classification model from tashiten. 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 17, 2026
- Updated
- Apr 17, 2026
- SHA
- 18bcda29
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Datasets
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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. -->
flower-vit-custom
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3003
- Accuracy: 0.96
- Precision: 0.9636
- Recall: 0.96
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.3106 | 1.0 | 222 | 0.4006 | 0.88 | 0.8902 | 0.88 |
| 0.1279 | 2.0 | 444 | 0.4271 | 0.88 | 0.8866 | 0.88 |
| 0.0408 | 3.0 | 666 | 0.3003 | 0.96 | 0.9636 | 0.96 |
| 0.0084 | 4.0 | 888 | 0.6091 | 0.86 | 0.8599 | 0.86 |
| 0.0012 | 5.0 | 1110 | 0.5942 | 0.88 | 0.8786 | 0.88 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.11.0
- Datasets 4.8.4
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 17, 2026
- Updated
- Apr 17, 2026