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vit-brain-tumour-v2
essam24/vit-brain-tumour-v2
vit-brain-tumour-v2 is a image classification model from essam24. Use it when you need a label for an image. 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
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024
- SHA
- 299cc864
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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. -->
vit-brain-tumour-v2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the essam24/brain-tumour-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5359
- Accuracy: 0.8704
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 |
|---|---|---|---|---|
| 0.1236 | 0.5128 | 100 | 0.5990 | 0.8481 |
| 0.1695 | 1.0256 | 200 | 0.5359 | 0.8704 |
| 0.0186 | 1.5385 | 300 | 0.5705 | 0.8975 |
| 0.0368 | 2.0513 | 400 | 0.6136 | 0.8975 |
| 0.0036 | 2.5641 | 500 | 0.6122 | 0.9012 |
| 0.0029 | 3.0769 | 600 | 0.6067 | 0.9025 |
| 0.0027 | 3.5897 | 700 | 0.6449 | 0.9025 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Image Classification
- Type
- vit
- License
- apache-2.0
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024