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Yogesh1p
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swin-tiny-patch4-window7-224-finetuned-cp3

Image Classification
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  1. README.md +13 -7
  2. model.safetensors +1 -1
  3. runs/Nov20_05-20-27_6d0e60f01160/events.out.tfevents.1700457629.6d0e60f01160.8784.1 +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: 0.6785714285714286
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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: 0.8002
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- - Accuracy: 0.6786
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  ## Model description
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@@ -61,15 +61,21 @@ 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 | 4 | 0.8642 | 0.6786 |
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- | No log | 2.0 | 8 | 0.8012 | 0.6786 |
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- | 0.8664 | 3.0 | 12 | 0.8002 | 0.6786 |
 
 
 
 
 
 
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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: 0.6964285714285714
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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: 0.7260
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+ - Accuracy: 0.6964
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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: 9
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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 | 4 | 0.8084 | 0.6786 |
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+ | No log | 2.0 | 8 | 0.8043 | 0.6964 |
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+ | 0.7014 | 3.0 | 12 | 0.8072 | 0.6964 |
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+ | 0.7014 | 4.0 | 16 | 0.7646 | 0.7321 |
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+ | 0.5379 | 5.0 | 20 | 0.7575 | 0.6964 |
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+ | 0.5379 | 6.0 | 24 | 0.6960 | 0.75 |
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+ | 0.5379 | 7.0 | 28 | 0.7306 | 0.6964 |
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+ | 0.5404 | 8.0 | 32 | 0.7448 | 0.6964 |
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+ | 0.5404 | 9.0 | 36 | 0.7260 | 0.6964 |
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  ### Framework versions
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