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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 +14 -14
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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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
@@ -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: 0.0492
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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
@@ -84,4 +84,4 @@ The following hyperparameters were used during training:
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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
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9798083504449008
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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: 0.0639
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+ - Accuracy: 0.9798
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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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+ | 0.337 | 1.0 | 205 | 0.2108 | 0.9175 |
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+ | 0.196 | 2.0 | 411 | 0.1137 | 0.9620 |
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+ | 0.1502 | 3.0 | 616 | 0.1030 | 0.9668 |
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+ | 0.1476 | 4.0 | 822 | 0.0815 | 0.9736 |
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+ | 0.1532 | 5.0 | 1027 | 0.0815 | 0.9760 |
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+ | 0.1311 | 6.0 | 1233 | 0.0667 | 0.9805 |
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+ | 0.1212 | 7.0 | 1438 | 0.0675 | 0.9805 |
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+ | 0.1637 | 8.0 | 1644 | 0.0697 | 0.9798 |
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+ | 0.116 | 9.0 | 1849 | 0.0638 | 0.9812 |
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+ | 0.085 | 9.98 | 2050 | 0.0639 | 0.9798 |
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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 0.14.1
pytorch_model.bin CHANGED
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