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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: 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: 0.961038961038961 |
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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: 0.0747 |
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- Accuracy: 0.9610 |
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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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| No log | 1.0 | 5 | 0.6616 | 0.6299 | |
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| 0.6583 | 2.0 | 10 | 0.5232 | 0.7597 | |
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| 0.6583 | 3.0 | 15 | 0.5043 | 0.7857 | |
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| 0.3346 | 4.0 | 20 | 0.2879 | 0.8766 | |
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| 0.3346 | 5.0 | 25 | 0.2424 | 0.9091 | |
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| 0.1544 | 6.0 | 30 | 0.2217 | 0.8896 | |
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| 0.1544 | 7.0 | 35 | 0.1466 | 0.9221 | |
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| 0.088 | 8.0 | 40 | 0.1261 | 0.9481 | |
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| 0.088 | 9.0 | 45 | 0.1680 | 0.9221 | |
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| 0.0977 | 10.0 | 50 | 0.1446 | 0.9351 | |
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| 0.0977 | 11.0 | 55 | 0.1812 | 0.9221 | |
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| 0.0719 | 12.0 | 60 | 0.1798 | 0.9286 | |
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| 0.0719 | 13.0 | 65 | 0.1056 | 0.9610 | |
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| 0.0629 | 14.0 | 70 | 0.1073 | 0.9675 | |
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| 0.0629 | 15.0 | 75 | 0.1106 | 0.9545 | |
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| 0.0414 | 16.0 | 80 | 0.1286 | 0.9416 | |
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| 0.0414 | 17.0 | 85 | 0.0761 | 0.9610 | |
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| 0.0397 | 18.0 | 90 | 0.0785 | 0.9675 | |
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| 0.0397 | 19.0 | 95 | 0.0746 | 0.9675 | |
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| 0.0487 | 20.0 | 100 | 0.0684 | 0.9675 | |
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| 0.0487 | 21.0 | 105 | 0.0602 | 0.9610 | |
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| 0.0244 | 22.0 | 110 | 0.0551 | 0.9675 | |
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| 0.0244 | 23.0 | 115 | 0.0639 | 0.9675 | |
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| 0.0214 | 24.0 | 120 | 0.0583 | 0.9675 | |
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| 0.0214 | 25.0 | 125 | 0.0663 | 0.9675 | |
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| 0.0261 | 26.0 | 130 | 0.1006 | 0.9610 | |
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| 0.0261 | 27.0 | 135 | 0.0711 | 0.9675 | |
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| 0.019 | 28.0 | 140 | 0.0629 | 0.9675 | |
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| 0.019 | 29.0 | 145 | 0.0728 | 0.9610 | |
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| 0.0237 | 30.0 | 150 | 0.0747 | 0.9610 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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