vit-skin-demo-v1
This model is a fine-tuned version of google/vit-base-patch16-224 on the skin-cancer dataset. It achieves the following results on the evaluation set:
- Loss: 0.4302
- Accuracy: 0.8558
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7377 | 0.31 | 100 | 0.7305 | 0.7553 |
0.8988 | 0.62 | 200 | 0.6799 | 0.7541 |
0.7157 | 0.93 | 300 | 0.6039 | 0.7772 |
0.5569 | 1.25 | 400 | 0.6506 | 0.7578 |
0.5342 | 1.56 | 500 | 0.5929 | 0.7846 |
0.6498 | 1.87 | 600 | 0.5553 | 0.7953 |
0.4956 | 2.18 | 700 | 0.5429 | 0.7921 |
0.5216 | 2.49 | 800 | 0.4704 | 0.8302 |
0.3468 | 2.8 | 900 | 0.4669 | 0.8327 |
0.4862 | 3.12 | 1000 | 0.4615 | 0.8421 |
0.4018 | 3.43 | 1100 | 0.4526 | 0.8458 |
0.302 | 3.74 | 1200 | 0.4302 | 0.8558 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for sharren/vit-skin-demo-v1
Base model
google/vit-base-patch16-224