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deit-base-patch16-224-bloodmnist-fold-10
selmamalak/deit-base-patch16-224-bloodmnist-fold-10
deit-base-patch16-224-bloodmnist-fold-10 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
- 2ec97c74
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-10
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: 0.0952
- Accuracy: 0.9666
- Precision: 0.9626
- Recall: 0.9642
- F1: 0.9632
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 |
|---|---|---|---|---|---|---|---|
| 0.5073 | 1.0 | 196 | 0.2655 | 0.9131 | 0.9163 | 0.8906 | 0.8959 |
| 0.4304 | 2.0 | 392 | 0.2909 | 0.8973 | 0.8787 | 0.8932 | 0.8798 |
| 0.3795 | 3.0 | 588 | 0.2452 | 0.9122 | 0.9398 | 0.8770 | 0.8974 |
| 0.3714 | 4.0 | 784 | 0.1538 | 0.9421 | 0.9354 | 0.9347 | 0.9345 |
| 0.3081 | 5.0 | 980 | 0.2068 | 0.9219 | 0.9148 | 0.9313 | 0.9180 |
| 0.2743 | 6.0 | 1176 | 0.1469 | 0.9482 | 0.9387 | 0.9458 | 0.9403 |
| 0.2371 | 7.0 | 1372 | 0.1209 | 0.9605 | 0.9596 | 0.9522 | 0.9551 |
| 0.2088 | 8.0 | 1568 | 0.1125 | 0.9579 | 0.9540 | 0.9496 | 0.9516 |
| 0.2071 | 9.0 | 1764 | 0.1160 | 0.9605 | 0.9568 | 0.9556 | 0.9553 |
| 0.1365 | 10.0 | 1960 | 0.0952 | 0.9666 | 0.9626 | 0.9642 | 0.9632 |
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