vit-skin-demo-v2
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: 0.5206
- Accuracy: 0.8027
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: cosine
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.749 | 0.31 | 100 | 0.8017 | 0.7322 |
0.7376 | 0.62 | 200 | 0.7833 | 0.7210 |
0.6393 | 0.93 | 300 | 0.7435 | 0.7453 |
0.6058 | 1.25 | 400 | 0.8366 | 0.7391 |
0.5794 | 1.56 | 500 | 0.7278 | 0.7597 |
0.6625 | 1.87 | 600 | 0.6116 | 0.7846 |
0.5256 | 2.18 | 700 | 0.6108 | 0.7759 |
0.6053 | 2.49 | 800 | 0.5631 | 0.7965 |
0.601 | 2.8 | 900 | 0.5206 | 0.8027 |
0.4709 | 3.12 | 1000 | 0.5477 | 0.8177 |
0.5498 | 3.43 | 1100 | 0.5426 | 0.8121 |
0.4196 | 3.74 | 1200 | 0.5652 | 0.8065 |
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-v2
Base model
google/vit-base-patch16-224