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--- |
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license: apache-2.0 |
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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-shortSleeveCleanedData |
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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: train |
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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: 0.994535519125683 |
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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-shortSleeveCleanedData |
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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: 0.0355 |
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- Accuracy: 0.9945 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 7 |
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- total_train_batch_size: 56 |
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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: 0.01 |
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- num_epochs: 20 |
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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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| 0.1819 | 1.0 | 147 | 0.0471 | 0.9880 | |
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| 0.1431 | 2.0 | 294 | 0.0457 | 0.9891 | |
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| 0.1001 | 3.0 | 441 | 0.0392 | 0.9891 | |
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| 0.116 | 4.0 | 588 | 0.0451 | 0.9880 | |
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| 0.1144 | 5.0 | 735 | 0.0398 | 0.9902 | |
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| 0.0787 | 6.0 | 882 | 0.0441 | 0.9902 | |
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| 0.0998 | 7.0 | 1029 | 0.0320 | 0.9902 | |
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| 0.124 | 8.0 | 1176 | 0.0364 | 0.9902 | |
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| 0.103 | 9.0 | 1323 | 0.0395 | 0.9880 | |
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| 0.0591 | 10.0 | 1470 | 0.0299 | 0.9913 | |
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| 0.0445 | 11.0 | 1617 | 0.0302 | 0.9913 | |
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| 0.0684 | 12.0 | 1764 | 0.0350 | 0.9880 | |
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| 0.0358 | 13.0 | 1911 | 0.0408 | 0.9891 | |
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| 0.0548 | 14.0 | 2058 | 0.0382 | 0.9902 | |
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| 0.0611 | 15.0 | 2205 | 0.0331 | 0.9923 | |
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| 0.0231 | 16.0 | 2352 | 0.0355 | 0.9945 | |
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| 0.046 | 17.0 | 2499 | 0.0321 | 0.9934 | |
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| 0.0648 | 18.0 | 2646 | 0.0327 | 0.9923 | |
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| 0.0565 | 19.0 | 2793 | 0.0320 | 0.9923 | |
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| 0.0413 | 20.0 | 2940 | 0.0327 | 0.9923 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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