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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-fold1 |
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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-fold1 |
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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: 0.1102 |
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- Accuracy: 0.9607 |
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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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| 0.9214 | 0.9714 | 17 | 0.7237 | 0.7249 | |
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| 0.5441 | 2.0 | 35 | 0.3606 | 0.8523 | |
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| 0.3592 | 2.9714 | 52 | 0.2474 | 0.9024 | |
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| 0.2732 | 4.0 | 70 | 0.2265 | 0.9173 | |
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| 0.2283 | 4.9714 | 87 | 0.1731 | 0.9404 | |
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| 0.1865 | 6.0 | 105 | 0.1808 | 0.9309 | |
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| 0.185 | 6.9714 | 122 | 0.1703 | 0.9201 | |
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| 0.1597 | 8.0 | 140 | 0.1262 | 0.9485 | |
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| 0.1545 | 8.9714 | 157 | 0.1375 | 0.9472 | |
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| 0.1237 | 10.0 | 175 | 0.1133 | 0.9580 | |
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| 0.1165 | 10.9714 | 192 | 0.1299 | 0.9512 | |
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| 0.1086 | 12.0 | 210 | 0.1118 | 0.9634 | |
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| 0.1129 | 12.9714 | 227 | 0.1101 | 0.9580 | |
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| 0.0898 | 14.0 | 245 | 0.1089 | 0.9607 | |
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| 0.0811 | 14.5714 | 255 | 0.1102 | 0.9607 | |
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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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