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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: 0.9100719424460432 |
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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: 0.2633 |
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- Accuracy: 0.9101 |
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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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| 0.8026 | 0.96 | 19 | 0.9313 | 0.5612 | |
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| 0.7571 | 1.97 | 39 | 0.8835 | 0.5755 | |
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| 0.7061 | 2.99 | 59 | 0.7589 | 0.6871 | |
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| 0.5911 | 4.0 | 79 | 0.6329 | 0.7482 | |
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| 0.5194 | 4.96 | 98 | 0.5634 | 0.7698 | |
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| 0.4471 | 5.97 | 118 | 0.4552 | 0.8165 | |
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| 0.3743 | 6.99 | 138 | 0.3760 | 0.8525 | |
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| 0.3686 | 8.0 | 158 | 0.3233 | 0.8705 | |
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| 0.318 | 8.96 | 177 | 0.3141 | 0.8777 | |
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| 0.3163 | 9.97 | 197 | 0.2772 | 0.8993 | |
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| 0.2871 | 10.99 | 217 | 0.2707 | 0.9029 | |
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| 0.2909 | 11.54 | 228 | 0.2633 | 0.9101 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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