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pyb-camag
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swin-tiny-patch4-window7-224-finetuned-ginger

Image Classification
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swin
Generated from Trainer
Eval Results
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  1. README.md +18 -9
  2. model.safetensors +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.5104591836734694
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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
@@ -33,8 +33,8 @@ 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: 1.3372
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- - Accuracy: 0.5105
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  ## Model description
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@@ -62,15 +62,24 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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- | 0.241 | 0.9973 | 275 | 1.5233 | 0.5110 |
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- | 0.1661 | 1.9982 | 551 | 1.3873 | 0.5242 |
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- | 0.1177 | 2.9918 | 825 | 1.3372 | 0.5105 |
 
 
 
 
 
 
 
 
 
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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: 0.7112244897959183
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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: 0.6161
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+ - Accuracy: 0.7112
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 12
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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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+ | 0.2795 | 0.9973 | 275 | 0.8344 | 0.7773 |
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+ | 0.1696 | 1.9982 | 551 | 1.2580 | 0.6245 |
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+ | 0.1425 | 2.9991 | 827 | 1.0643 | 0.5959 |
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+ | 0.1329 | 4.0 | 1103 | 0.8342 | 0.6281 |
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+ | 0.1237 | 4.9973 | 1378 | 1.4786 | 0.6110 |
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+ | 0.0743 | 5.9982 | 1654 | 1.1068 | 0.6283 |
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+ | 0.1083 | 6.9991 | 1930 | 0.8262 | 0.8321 |
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+ | 0.0667 | 8.0 | 2206 | 0.6214 | 0.7564 |
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+ | 0.0743 | 8.9973 | 2481 | 0.7777 | 0.7342 |
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+ | 0.0527 | 9.9982 | 2757 | 0.6794 | 0.6985 |
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+ | 0.076 | 10.9991 | 3033 | 0.7436 | 0.6429 |
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+ | 0.0423 | 11.9674 | 3300 | 0.6161 | 0.7112 |
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  ### Framework versions
model.safetensors CHANGED
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