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deit-base-patch16-224-bloodmnist-fold-7
selmamalak/deit-base-patch16-224-bloodmnist-fold-7
deit-base-patch16-224-bloodmnist-fold-7 is a machine learning model from selmamalak. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. 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
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Jul 21, 2025
- Updated
- Jul 21, 2025
- SHA
- 4e7ec5c1
Base models
Datasets
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. -->
deit-base-patch16-224-bloodmnist-fold-7
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the medmnist-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0664
- Accuracy: 0.9728
- Precision: 0.9705
- Recall: 0.9702
- F1: 0.9703
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: 0.005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5419 | 1.0 | 196 | 0.2200 | 0.9175 | 0.9024 | 0.9144 | 0.9045 |
| 0.4608 | 2.0 | 392 | 0.3279 | 0.8850 | 0.8661 | 0.8958 | 0.8693 |
| 0.3754 | 3.0 | 588 | 0.2011 | 0.9447 | 0.9364 | 0.9404 | 0.9374 |
| 0.3761 | 4.0 | 784 | 0.2441 | 0.9245 | 0.9251 | 0.9274 | 0.9197 |
| 0.3318 | 5.0 | 980 | 0.1537 | 0.9473 | 0.9572 | 0.9326 | 0.9402 |
| 0.3005 | 6.0 | 1176 | 0.1209 | 0.9587 | 0.9547 | 0.9457 | 0.9490 |
| 0.2362 | 7.0 | 1372 | 0.1102 | 0.9535 | 0.9526 | 0.9473 | 0.9492 |
| 0.1691 | 8.0 | 1568 | 0.0943 | 0.9622 | 0.9572 | 0.9555 | 0.9558 |
| 0.1631 | 9.0 | 1764 | 0.0776 | 0.9675 | 0.9635 | 0.9639 | 0.9634 |
| 0.0905 | 10.0 | 1960 | 0.0664 | 0.9728 | 0.9705 | 0.9702 | 0.9703 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Library
- peft
- License
- apache-2.0
- Created
- Jul 21, 2025
- Updated
- Jul 21, 2025