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derma-vit-base-finetuned
selmamalak/derma-vit-base-finetuned
derma-vit-base-finetuned 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
- Mar 14, 2024
- Updated
- Mar 14, 2024
- SHA
- 88e12286
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. -->
derma-vit-base-finetuned
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the medmnist-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6135
- Accuracy: 0.7681
- Precision: 0.6821
- Recall: 0.5061
- F1: 0.5497
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7579 | 1.0 | 109 | 0.7045 | 0.7428 | 0.5204 | 0.3710 | 0.3927 |
| 0.7689 | 2.0 | 219 | 0.7512 | 0.7278 | 0.3964 | 0.3527 | 0.3573 |
| 0.7353 | 3.0 | 328 | 0.7191 | 0.7358 | 0.4630 | 0.4202 | 0.4002 |
| 0.8429 | 4.0 | 438 | 0.7858 | 0.6810 | 0.4280 | 0.1813 | 0.1851 |
| 0.7929 | 5.0 | 547 | 0.7013 | 0.7218 | 0.5158 | 0.3971 | 0.3523 |
| 0.6804 | 6.0 | 657 | 0.6822 | 0.7607 | 0.5011 | 0.4240 | 0.4391 |
| 0.6922 | 7.0 | 766 | 0.6533 | 0.7667 | 0.6762 | 0.5106 | 0.5227 |
| 0.6563 | 8.0 | 876 | 0.6758 | 0.7468 | 0.4548 | 0.4589 | 0.4496 |
| 0.6985 | 9.0 | 985 | 0.6264 | 0.7647 | 0.6451 | 0.4692 | 0.4915 |
| 0.6283 | 9.95 | 1090 | 0.6179 | 0.7677 | 0.5889 | 0.4796 | 0.5088 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- peft
- License
- apache-2.0
- Created
- Mar 14, 2024
- Updated
- Mar 14, 2024