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deit-base-patch16-224-bloodmnist-fold-11
selmamalak/deit-base-patch16-224-bloodmnist-fold-11
deit-base-patch16-224-bloodmnist-fold-11 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
- 8b6809a6
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-11
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: 0.0698
- Accuracy: 0.9719
- Precision: 0.9700
- Recall: 0.9660
- F1: 0.9678
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 |
|---|---|---|---|---|---|---|---|
| 0.5069 | 1.0 | 196 | 0.2816 | 0.8999 | 0.8951 | 0.8753 | 0.8751 |
| 0.3466 | 2.0 | 392 | 0.4097 | 0.8753 | 0.8562 | 0.8715 | 0.8503 |
| 0.3809 | 3.0 | 588 | 0.2836 | 0.8832 | 0.9151 | 0.8482 | 0.8613 |
| 0.3266 | 4.0 | 784 | 0.1781 | 0.9385 | 0.9303 | 0.9293 | 0.9266 |
| 0.3099 | 5.0 | 980 | 0.1826 | 0.9315 | 0.9471 | 0.9162 | 0.9273 |
| 0.2418 | 6.0 | 1176 | 0.1171 | 0.9543 | 0.9480 | 0.9559 | 0.9504 |
| 0.2167 | 7.0 | 1372 | 0.1141 | 0.9579 | 0.9609 | 0.9432 | 0.9503 |
| 0.1683 | 8.0 | 1568 | 0.1165 | 0.9587 | 0.9678 | 0.9454 | 0.9539 |
| 0.1491 | 9.0 | 1764 | 0.0844 | 0.9701 | 0.9743 | 0.9579 | 0.9650 |
| 0.1142 | 10.0 | 1960 | 0.0698 | 0.9719 | 0.9700 | 0.9660 | 0.9678 |
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