| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/swin-tiny-patch4-window7-224 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-brain-abnormalities-classification |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # swin-brain-abnormalities-classification |
|
|
| This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2461 |
| - Accuracy: 0.9273 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | 0.928 | 0.9892 | 23 | 0.6080 | 0.7705 | |
| | 0.508 | 1.9785 | 46 | 0.2402 | 0.9162 | |
| | 0.3178 | 2.9677 | 69 | 0.2121 | 0.9246 | |
| | 0.2338 | 4.0 | 93 | 0.2045 | 0.9363 | |
| | 0.1788 | 4.9892 | 116 | 0.2443 | 0.9296 | |
| | 0.1675 | 5.9785 | 139 | 0.1457 | 0.9430 | |
| | 0.155 | 6.9677 | 162 | 0.1708 | 0.9514 | |
| | 0.1316 | 8.0 | 186 | 0.1555 | 0.9531 | |
| | 0.1099 | 8.9892 | 209 | 0.1732 | 0.9531 | |
| | 0.1121 | 9.9785 | 232 | 0.1358 | 0.9581 | |
| | 0.1007 | 10.9677 | 255 | 0.2155 | 0.9514 | |
| | 0.0951 | 12.0 | 279 | 0.1506 | 0.9648 | |
| | 0.0841 | 12.9892 | 302 | 0.1921 | 0.9531 | |
| | 0.0778 | 13.9785 | 325 | 0.2041 | 0.9531 | |
| | 0.0768 | 14.8387 | 345 | 0.1909 | 0.9548 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.45.1 |
| - Pytorch 2.4.0 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
|
|
