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bombshelll
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swin-brain-plane-classification

Image Classification
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Safetensors
swin
Generated from Trainer
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0630
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- - Accuracy: 0.9852
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  ## Model description
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@@ -47,21 +47,22 @@ 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: 20
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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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- | 1.0732 | 1.0 | 5 | 0.9285 | 0.6667 |
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- | 0.829 | 2.0 | 10 | 0.5274 | 0.8593 |
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- | 0.5189 | 3.0 | 15 | 0.2473 | 0.9333 |
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- | 0.3517 | 4.0 | 20 | 0.1405 | 0.9630 |
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- | 0.2075 | 5.0 | 25 | 0.1797 | 0.9333 |
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- | 0.1871 | 6.0 | 30 | 0.0936 | 0.9704 |
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- | 0.1567 | 7.0 | 35 | 0.1113 | 0.9704 |
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- | 0.1482 | 8.0 | 40 | 0.0791 | 0.9778 |
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- | 0.1143 | 9.0 | 45 | 0.0630 | 0.9852 |
 
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  ### Framework versions
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0496
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+ - Accuracy: 0.9778
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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: 10
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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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+ | 1.0282 | 1.0 | 5 | 0.7965 | 0.7111 |
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+ | 0.6572 | 2.0 | 10 | 0.3109 | 0.9630 |
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+ | 0.3913 | 3.0 | 15 | 0.1849 | 0.9630 |
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+ | 0.2707 | 4.0 | 20 | 0.1380 | 0.9630 |
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+ | 0.1767 | 5.0 | 25 | 0.0945 | 0.9704 |
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+ | 0.1469 | 6.0 | 30 | 0.0885 | 0.9704 |
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+ | 0.1316 | 7.0 | 35 | 0.0735 | 0.9778 |
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+ | 0.1272 | 8.0 | 40 | 0.0705 | 0.9778 |
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+ | 0.1116 | 9.0 | 45 | 0.0514 | 0.9778 |
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+ | 0.1114 | 10.0 | 50 | 0.0496 | 0.9778 |
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  ### Framework versions
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