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--- |
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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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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-finetuned-rsna-2018 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7410179640718563 |
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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-tiny-patch4-window7-224-finetuned-rsna-2018 |
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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 the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5745 |
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- Accuracy: 0.7410 |
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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: 30 |
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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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| 0.6448 | 0.9940 | 83 | 0.6735 | 0.6737 | |
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| 0.736 | 2.0 | 167 | 0.6969 | 0.6557 | |
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| 0.6895 | 2.9940 | 250 | 0.6265 | 0.6916 | |
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| 0.6631 | 4.0 | 334 | 0.6275 | 0.7156 | |
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| 0.6725 | 4.9940 | 417 | 0.6311 | 0.7126 | |
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| 0.6778 | 6.0 | 501 | 0.6194 | 0.7066 | |
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| 0.6734 | 6.9940 | 584 | 0.6024 | 0.7141 | |
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| 0.6231 | 8.0 | 668 | 0.6082 | 0.7231 | |
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| 0.6164 | 8.9940 | 751 | 0.5846 | 0.7171 | |
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| 0.6261 | 10.0 | 835 | 0.5682 | 0.7380 | |
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| 0.6153 | 10.9940 | 918 | 0.6007 | 0.7186 | |
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| 0.6046 | 12.0 | 1002 | 0.5745 | 0.7410 | |
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| 0.5679 | 12.9940 | 1085 | 0.5957 | 0.7231 | |
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| 0.6027 | 14.0 | 1169 | 0.5884 | 0.7216 | |
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| 0.6249 | 14.9940 | 1252 | 0.5808 | 0.7365 | |
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| 0.6059 | 16.0 | 1336 | 0.5699 | 0.7350 | |
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| 0.5776 | 16.9940 | 1419 | 0.5770 | 0.7320 | |
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| 0.5903 | 18.0 | 1503 | 0.5806 | 0.7216 | |
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| 0.5633 | 18.9940 | 1586 | 0.5768 | 0.7380 | |
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| 0.5544 | 20.0 | 1670 | 0.5830 | 0.7350 | |
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| 0.5515 | 20.9940 | 1753 | 0.5966 | 0.7260 | |
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| 0.5249 | 22.0 | 1837 | 0.6079 | 0.7335 | |
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| 0.5212 | 22.9940 | 1920 | 0.5972 | 0.7246 | |
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| 0.5268 | 24.0 | 2004 | 0.5922 | 0.7231 | |
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| 0.5406 | 24.9940 | 2087 | 0.6100 | 0.7350 | |
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| 0.5257 | 26.0 | 2171 | 0.6004 | 0.7305 | |
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| 0.5152 | 26.9940 | 2254 | 0.6092 | 0.7320 | |
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| 0.4858 | 28.0 | 2338 | 0.6100 | 0.7231 | |
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| 0.5412 | 28.9940 | 2421 | 0.6116 | 0.7350 | |
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| 0.4972 | 29.8204 | 2490 | 0.6120 | 0.7290 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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