vit-skin-demo-v3
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: 0.4066
- Accuracy: 0.8517
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 |
---|---|---|---|---|
0.6938 | 0.31 | 100 | 0.9315 | 0.6523 |
0.7574 | 0.62 | 200 | 0.9532 | 0.6404 |
0.6163 | 0.93 | 300 | 0.6160 | 0.7728 |
0.4747 | 1.25 | 400 | 0.6093 | 0.7940 |
0.4771 | 1.56 | 500 | 0.6314 | 0.7772 |
0.5632 | 1.87 | 600 | 0.6300 | 0.7559 |
0.4049 | 2.18 | 700 | 0.4991 | 0.8146 |
0.5362 | 2.49 | 800 | 0.4934 | 0.8215 |
0.4617 | 2.8 | 900 | 0.4625 | 0.8390 |
0.2861 | 3.12 | 1000 | 0.4361 | 0.8464 |
0.3559 | 3.43 | 1100 | 0.4040 | 0.8608 |
0.2876 | 3.74 | 1200 | 0.3846 | 0.8702 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Base model
google/vit-base-patch16-224