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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-brain-abnormalities-classification |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# swin-brain-abnormalities-classification |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2461 |
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- Accuracy: 0.9273 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 0.928 | 0.9892 | 23 | 0.6080 | 0.7705 | |
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| 0.508 | 1.9785 | 46 | 0.2402 | 0.9162 | |
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| 0.3178 | 2.9677 | 69 | 0.2121 | 0.9246 | |
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| 0.2338 | 4.0 | 93 | 0.2045 | 0.9363 | |
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| 0.1788 | 4.9892 | 116 | 0.2443 | 0.9296 | |
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| 0.1675 | 5.9785 | 139 | 0.1457 | 0.9430 | |
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| 0.155 | 6.9677 | 162 | 0.1708 | 0.9514 | |
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| 0.1316 | 8.0 | 186 | 0.1555 | 0.9531 | |
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| 0.1099 | 8.9892 | 209 | 0.1732 | 0.9531 | |
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| 0.1121 | 9.9785 | 232 | 0.1358 | 0.9581 | |
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| 0.1007 | 10.9677 | 255 | 0.2155 | 0.9514 | |
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| 0.0951 | 12.0 | 279 | 0.1506 | 0.9648 | |
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| 0.0841 | 12.9892 | 302 | 0.1921 | 0.9531 | |
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| 0.0778 | 13.9785 | 325 | 0.2041 | 0.9531 | |
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| 0.0768 | 14.8387 | 345 | 0.1909 | 0.9548 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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