vit-brain-tumour-v1
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the essam24/brain-tumour-v1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0044
- Accuracy: 1.0
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 |
|---|---|---|---|---|
| 0.0043 | 2.7027 | 100 | 0.0044 | 1.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for essam24/vit-brain-tumour-v1
Base model
google/vit-base-patch16-224-in21kSpace using essam24/vit-brain-tumour-v1 1
Evaluation results
- Accuracy on essam24/brain-tumour-v1test set self-reported1.000