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Browse files- README.md +22 -7
- model.safetensors +1 -1
README.md
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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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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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---
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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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# 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
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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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: 0.9852941176470589
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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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# 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: 0.0427
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- Accuracy: 0.9853
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.121 | 1.0 | 374 | 0.0898 | 0.9662 |
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| 0.0766 | 2.0 | 748 | 0.0427 | 0.9853 |
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| 0.0674 | 3.0 | 1122 | 0.0427 | 0.9853 |
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### Framework versions
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model.safetensors
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