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NiharGupte
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swin-tiny-patch4-window7-224-finetuned-student_six_classes

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  1. README.md +14 -7
  2. model.safetensors +1 -1
  3. runs/Apr15_01-25-06_076be6699dc0/events.out.tfevents.1713144313.076be6699dc0.466.3 +2 -2
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: 0.7751572327044025
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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: 0.4916
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- - Accuracy: 0.7752
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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: 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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- | 1.4387 | 0.94 | 11 | 0.9083 | 0.6368 |
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- | 0.7445 | 1.96 | 23 | 0.5326 | 0.8553 |
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- | 0.4879 | 2.81 | 33 | 0.4916 | 0.7752 |
 
 
 
 
 
 
 
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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: 0.9512578616352201
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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: 0.1187
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+ - Accuracy: 0.9513
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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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+ | 1.619 | 0.94 | 11 | 1.1587 | 0.4984 |
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+ | 0.841 | 1.96 | 23 | 0.5082 | 0.7689 |
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+ | 0.4154 | 2.98 | 35 | 0.2849 | 0.8868 |
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+ | 0.3476 | 4.0 | 47 | 0.2089 | 0.9418 |
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+ | 0.2414 | 4.94 | 58 | 0.1575 | 0.9450 |
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+ | 0.2128 | 5.96 | 70 | 0.1226 | 0.9497 |
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+ | 0.1783 | 6.98 | 82 | 0.1203 | 0.9481 |
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+ | 0.167 | 8.0 | 94 | 0.1169 | 0.9528 |
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+ | 0.1723 | 8.94 | 105 | 0.1184 | 0.9513 |
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+ | 0.1838 | 9.36 | 110 | 0.1187 | 0.9513 |
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  ### Framework versions
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