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HorcruxNo13
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swin-tiny-patch4-window7-224

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Eval Results (legacy)
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  1. README.md +11 -7
  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: 0.73
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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: 0.5407
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- - Accuracy: 0.73
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  ## Model description
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@@ -61,15 +61,19 @@ The following hyperparameters were used during training:
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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: 3
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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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- | No log | 1.0 | 8 | 0.5740 | 0.7333 |
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- | 0.6033 | 2.0 | 16 | 0.5640 | 0.7333 |
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- | 0.5751 | 3.0 | 24 | 0.5568 | 0.7375 |
 
 
 
 
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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: 0.7366666666666667
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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: 0.5300
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+ - Accuracy: 0.7367
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  ## Model description
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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: 7
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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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+ | No log | 1.0 | 8 | 0.5816 | 0.7333 |
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+ | 0.6478 | 2.0 | 16 | 0.5634 | 0.7333 |
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+ | 0.5746 | 3.0 | 24 | 0.5526 | 0.7375 |
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+ | 0.5414 | 4.0 | 32 | 0.6044 | 0.7333 |
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+ | 0.5159 | 5.0 | 40 | 0.5310 | 0.7542 |
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+ | 0.5159 | 6.0 | 48 | 0.5481 | 0.7583 |
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+ | 0.4901 | 7.0 | 56 | 0.5410 | 0.7583 |
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  ### Framework versions
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