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finetuned-xray
jkfm/finetuned-xray
finetuned-xray is a image classification model from jkfm. 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 9, 2025
- Updated
- Oct 9, 2025
- SHA
- 799a81f8
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. -->
finetuned-xray
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the xray-images dataset. It achieves the following results on the evaluation set:
- Loss: 0.0206
- Accuracy: 0.9940
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7605 | 0.2123 | 100 | 0.6921 | 0.5030 |
| 0.5794 | 0.4246 | 200 | 0.5186 | 0.7519 |
| 0.4215 | 0.6369 | 300 | 0.4524 | 0.7962 |
| 0.3343 | 0.8493 | 400 | 0.3058 | 0.8707 |
| 0.2716 | 1.0616 | 500 | 0.3114 | 0.8880 |
| 0.2027 | 1.2739 | 600 | 0.1684 | 0.9346 |
| 0.1439 | 1.4862 | 700 | 0.1283 | 0.9579 |
| 0.1269 | 1.6985 | 800 | 0.0816 | 0.9737 |
| 0.1247 | 1.9108 | 900 | 0.0920 | 0.9692 |
| 0.1696 | 2.1231 | 1000 | 0.0655 | 0.9767 |
| 0.1004 | 2.3355 | 1100 | 0.0612 | 0.9857 |
| 0.0748 | 2.5478 | 1200 | 0.0764 | 0.9797 |
| 0.1652 | 2.7601 | 1300 | 0.0355 | 0.9902 |
| 0.1129 | 2.9724 | 1400 | 0.0341 | 0.9917 |
| 0.0816 | 3.1847 | 1500 | 0.0511 | 0.9872 |
| 0.091 | 3.3970 | 1600 | 0.0475 | 0.9850 |
| 0.0778 | 3.6093 | 1700 | 0.0329 | 0.9902 |
| 0.111 | 3.8217 | 1800 | 0.0206 | 0.9940 |
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 9, 2025
- Updated
- Oct 9, 2025