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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-fold4 |
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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-fold4 |
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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: 0.1851 |
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- Accuracy: 0.9525 |
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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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| 0.8479 | 0.9714 | 17 | 0.6472 | 0.7368 | |
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| 0.5421 | 2.0 | 35 | 0.3346 | 0.8575 | |
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| 0.3307 | 2.9714 | 52 | 0.2288 | 0.9240 | |
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| 0.2351 | 4.0 | 70 | 0.2233 | 0.9254 | |
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| 0.2195 | 4.9714 | 87 | 0.2139 | 0.9322 | |
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| 0.1914 | 6.0 | 105 | 0.2227 | 0.9294 | |
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| 0.164 | 6.9714 | 122 | 0.1924 | 0.9389 | |
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| 0.1305 | 8.0 | 140 | 0.2340 | 0.9267 | |
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| 0.1526 | 8.9714 | 157 | 0.1705 | 0.9525 | |
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| 0.1188 | 10.0 | 175 | 0.1525 | 0.9539 | |
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| 0.125 | 10.9714 | 192 | 0.1693 | 0.9457 | |
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| 0.0927 | 12.0 | 210 | 0.1584 | 0.9552 | |
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| 0.0972 | 12.9714 | 227 | 0.1752 | 0.9512 | |
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| 0.0848 | 14.0 | 245 | 0.1806 | 0.9525 | |
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| 0.1119 | 14.5714 | 255 | 0.1851 | 0.9525 | |
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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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