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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-eurosat |
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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: 0.9383116883116883 |
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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-eurosat |
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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: 0.2469 |
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- Accuracy: 0.9383 |
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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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| 0.9843 | 0.99 | 43 | 0.8500 | 0.6948 | |
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| 0.5335 | 2.0 | 87 | 0.5584 | 0.7825 | |
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| 0.4263 | 2.99 | 130 | 0.4791 | 0.8117 | |
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| 0.3308 | 4.0 | 174 | 0.4269 | 0.8344 | |
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| 0.2882 | 4.99 | 217 | 0.3567 | 0.8636 | |
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| 0.2517 | 6.0 | 261 | 0.3317 | 0.8701 | |
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| 0.1908 | 6.99 | 304 | 0.3082 | 0.8815 | |
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| 0.187 | 8.0 | 348 | 0.3230 | 0.8799 | |
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| 0.1434 | 8.99 | 391 | 0.3323 | 0.9010 | |
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| 0.1277 | 10.0 | 435 | 0.2489 | 0.9075 | |
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| 0.156 | 10.99 | 478 | 0.3246 | 0.8880 | |
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| 0.0781 | 12.0 | 522 | 0.3121 | 0.9010 | |
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| 0.1001 | 12.99 | 565 | 0.2708 | 0.9058 | |
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| 0.0892 | 14.0 | 609 | 0.2582 | 0.9140 | |
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| 0.0644 | 14.99 | 652 | 0.2486 | 0.9221 | |
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| 0.0689 | 16.0 | 696 | 0.2465 | 0.9237 | |
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| 0.0547 | 16.99 | 739 | 0.2402 | 0.9334 | |
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| 0.0597 | 18.0 | 783 | 0.2534 | 0.9237 | |
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| 0.0512 | 18.99 | 826 | 0.2400 | 0.9318 | |
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| 0.041 | 20.0 | 870 | 0.2397 | 0.9286 | |
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| 0.0376 | 20.99 | 913 | 0.2663 | 0.9269 | |
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| 0.0412 | 22.0 | 957 | 0.3026 | 0.9221 | |
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| 0.0423 | 22.99 | 1000 | 0.2678 | 0.9302 | |
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| 0.0266 | 24.0 | 1044 | 0.2510 | 0.9318 | |
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| 0.0313 | 24.99 | 1087 | 0.2542 | 0.9334 | |
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| 0.0207 | 26.0 | 1131 | 0.2743 | 0.9334 | |
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| 0.0292 | 26.99 | 1174 | 0.2614 | 0.9318 | |
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| 0.0242 | 28.0 | 1218 | 0.2469 | 0.9383 | |
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| 0.0201 | 28.99 | 1261 | 0.2534 | 0.9367 | |
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| 0.0354 | 29.66 | 1290 | 0.2525 | 0.9367 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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