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100rab25
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swin-tiny-patch4-window7-224-spa_saloon_classification

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +15 -15
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.966893039049236
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.1131
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- - Accuracy: 0.9669
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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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- | 0.4613 | 1.0 | 83 | 0.3357 | 0.8718 |
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- | 0.2908 | 2.0 | 166 | 0.1805 | 0.9312 |
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- | 0.2341 | 3.0 | 249 | 0.1426 | 0.9516 |
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- | 0.1907 | 4.0 | 332 | 0.1471 | 0.9423 |
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- | 0.1836 | 5.0 | 415 | 0.1177 | 0.9576 |
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- | 0.1669 | 6.0 | 498 | 0.1131 | 0.9669 |
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- | 0.152 | 7.0 | 581 | 0.1100 | 0.9660 |
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- | 0.1666 | 8.0 | 664 | 0.1130 | 0.9626 |
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- | 0.1374 | 9.0 | 747 | 0.1132 | 0.9669 |
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- | 0.1278 | 10.0 | 830 | 0.1075 | 0.9652 |
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  ### Framework versions
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- - Transformers 4.33.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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- - Tokenizers 0.13.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9826023921710765
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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: 0.0492
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+ - Accuracy: 0.9826
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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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+ | 0.2851 | 1.0 | 194 | 0.1485 | 0.9507 |
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+ | 0.2143 | 2.0 | 388 | 0.0938 | 0.9677 |
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+ | 0.152 | 3.0 | 582 | 0.0833 | 0.9710 |
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+ | 0.1469 | 4.0 | 776 | 0.0692 | 0.9754 |
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+ | 0.1663 | 5.0 | 970 | 0.0611 | 0.9797 |
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+ | 0.1135 | 6.0 | 1164 | 0.0649 | 0.9783 |
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+ | 0.1155 | 7.0 | 1358 | 0.0525 | 0.9859 |
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+ | 0.1356 | 8.0 | 1552 | 0.0496 | 0.9851 |
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+ | 0.0895 | 9.0 | 1746 | 0.0497 | 0.9830 |
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+ | 0.1136 | 10.0 | 1940 | 0.0492 | 0.9826 |
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  ### Framework versions
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+ - Transformers 4.34.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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+ - Tokenizers 0.14.0
pytorch_model.bin CHANGED
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