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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-finetuned-main-gpu-20e-final |
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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: 0.9913265306122448 |
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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-main-gpu-20e-final |
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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: 0.0254 |
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- Accuracy: 0.9913 |
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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: 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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| 0.5767 | 1.0 | 551 | 0.5565 | 0.7463 | |
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| 0.3985 | 2.0 | 1102 | 0.3165 | 0.8711 | |
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| 0.2988 | 3.0 | 1653 | 0.1835 | 0.9293 | |
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| 0.2449 | 4.0 | 2204 | 0.1150 | 0.9572 | |
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| 0.2037 | 5.0 | 2755 | 0.0993 | 0.9632 | |
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| 0.1646 | 6.0 | 3306 | 0.0750 | 0.9717 | |
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| 0.1995 | 7.0 | 3857 | 0.0610 | 0.9776 | |
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| 0.1659 | 8.0 | 4408 | 0.0485 | 0.9815 | |
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| 0.1449 | 9.0 | 4959 | 0.0505 | 0.9821 | |
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| 0.1315 | 10.0 | 5510 | 0.0444 | 0.9843 | |
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| 0.102 | 11.0 | 6061 | 0.0440 | 0.9838 | |
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| 0.1039 | 12.0 | 6612 | 0.0359 | 0.9870 | |
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| 0.0798 | 13.0 | 7163 | 0.0393 | 0.9869 | |
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| 0.1033 | 14.0 | 7714 | 0.0343 | 0.9890 | |
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| 0.078 | 15.0 | 8265 | 0.0298 | 0.9902 | |
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| 0.0765 | 16.0 | 8816 | 0.0299 | 0.9901 | |
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| 0.0769 | 17.0 | 9367 | 0.0275 | 0.9908 | |
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| 0.0751 | 18.0 | 9918 | 0.0271 | 0.9910 | |
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| 0.0822 | 19.0 | 10469 | 0.0251 | 0.9917 | |
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| 0.0756 | 20.0 | 11020 | 0.0254 | 0.9913 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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