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melanoma-exp-E-optimal
oscar2525mv/melanoma-exp-E-optimal
melanoma-exp-E-optimal is a image classification model from oscar2525mv. 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
- Jan 7, 2026
- Updated
- Jan 7, 2026
- SHA
- 9fd384db
Base models
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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. -->
melanoma-exp-E-optimal
This model is a fine-tuned version of google/vit-base-patch16-384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2886
- Auc: 0.9096
- Accuracy: 0.8981
- Recall: 0.6082
- Specificity: 0.9414
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Auc | Accuracy | Recall | Specificity |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 267 | 0.3006 | 0.8758 | 0.8478 | 0.5825 | 0.8874 |
| 7.5432 | 2.0 | 534 | 0.2533 | 0.8956 | 0.8934 | 0.4742 | 0.9561 |
| 7.5432 | 3.0 | 801 | 0.2655 | 0.9070 | 0.8967 | 0.5619 | 0.9468 |
| 3.6167 | 4.0 | 1068 | 0.2929 | 0.9101 | 0.8846 | 0.6237 | 0.9237 |
| 3.6167 | 5.0 | 1335 | 0.2886 | 0.9096 | 0.8981 | 0.6082 | 0.9414 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.2
- Tokenizers 0.22.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jan 7, 2026
- Updated
- Jan 7, 2026