andrecastro
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Model save
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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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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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.
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- Accuracy: 0.
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- Precision: 0.
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- Recall: 0.
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- Confusion Matrix: [[
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9883021390374331
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- name: Precision
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type: precision
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value: 0.9883071765108582
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- name: Recall
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type: recall
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value: 0.9883021390374331
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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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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: 0.0394
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- Accuracy: 0.9883
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- Precision: 0.9883
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- Recall: 0.9883
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- Confusion Matrix: [[1497, 15], [20, 1460]]
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
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| 0.1107 | 1.0 | 374 | 0.0641 | 0.9786 | 0.9787 | 0.9786 | [[1488, 24], [40, 1440]] |
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| 0.1079 | 2.0 | 748 | 0.0560 | 0.9773 | 0.9776 | 0.9773 | [[1498, 14], [54, 1426]] |
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| 0.0624 | 3.0 | 1122 | 0.0394 | 0.9883 | 0.9883 | 0.9883 | [[1497, 15], [20, 1460]] |
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### Framework versions
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