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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-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: 0.9828042328042328 |
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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-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: 0.0684 |
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- Accuracy: 0.9828 |
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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: 10 |
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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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| 1.2075 | 0.98 | 33 | 0.5666 | 0.8519 | |
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| 0.2022 | 1.98 | 66 | 0.2523 | 0.9127 | |
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| 0.1206 | 2.98 | 99 | 0.1576 | 0.9497 | |
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| 0.0897 | 3.98 | 132 | 0.1421 | 0.9563 | |
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| 0.0564 | 4.98 | 165 | 0.1114 | 0.9656 | |
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| 0.0475 | 5.98 | 198 | 0.0678 | 0.9815 | |
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| 0.0332 | 6.98 | 231 | 0.0819 | 0.9775 | |
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| 0.0234 | 7.98 | 264 | 0.0679 | 0.9802 | |
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| 0.0126 | 8.98 | 297 | 0.0684 | 0.9828 | |
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| 0.0306 | 9.98 | 330 | 0.0719 | 0.9815 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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