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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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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-classification |
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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-tiny-patch4-window7-224-classification |
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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: 0.2787 |
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- Accuracy: 0.9264 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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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| 0.1469 | 1.0 | 100 | 0.3027 | 0.9127 | |
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| 0.1677 | 2.0 | 200 | 0.3351 | 0.9001 | |
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| 0.167 | 2.99 | 300 | 0.3875 | 0.8931 | |
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| 0.1556 | 4.0 | 401 | 0.3814 | 0.8969 | |
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| 0.1328 | 5.0 | 501 | 0.3281 | 0.9046 | |
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| 0.1 | 6.0 | 601 | 0.3726 | 0.9004 | |
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| 0.1188 | 6.99 | 701 | 0.3736 | 0.9046 | |
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| 0.1257 | 8.0 | 802 | 0.3381 | 0.9102 | |
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| 0.1017 | 9.0 | 902 | 0.2872 | 0.9215 | |
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| 0.0987 | 10.0 | 1002 | 0.3067 | 0.9176 | |
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| 0.0874 | 10.99 | 1102 | 0.2919 | 0.9165 | |
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| 0.0901 | 12.0 | 1203 | 0.2942 | 0.9229 | |
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| 0.0831 | 13.0 | 1303 | 0.2974 | 0.9232 | |
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| 0.0838 | 14.0 | 1403 | 0.2787 | 0.9264 | |
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| 0.0603 | 14.96 | 1500 | 0.2780 | 0.9264 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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