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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-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: 0.9341978866474544 |
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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: 0.1507 |
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- Accuracy: 0.9342 |
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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: 12 |
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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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| 0.2891 | 1.0 | 146 | 0.2322 | 0.9068 | |
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| 0.2609 | 2.0 | 292 | 0.1710 | 0.9227 | |
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| 0.2417 | 3.0 | 438 | 0.1830 | 0.9251 | |
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| 0.2406 | 4.0 | 584 | 0.1809 | 0.9198 | |
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| 0.2113 | 5.0 | 730 | 0.1631 | 0.9289 | |
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| 0.1812 | 6.0 | 876 | 0.1561 | 0.9308 | |
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| 0.2082 | 7.0 | 1022 | 0.1507 | 0.9342 | |
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| 0.1922 | 8.0 | 1168 | 0.1611 | 0.9294 | |
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| 0.1715 | 9.0 | 1314 | 0.1536 | 0.9308 | |
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| 0.1675 | 10.0 | 1460 | 0.1609 | 0.9289 | |
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| 0.194 | 11.0 | 1606 | 0.1499 | 0.9337 | |
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| 0.1706 | 12.0 | 1752 | 0.1514 | 0.9323 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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