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ravipratap366
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swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification

Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
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  1. README.md +17 -17
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 1.0
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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: 0.3943
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- - Accuracy: 1.0
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  ## Model description
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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 | 1 | 0.8506 | 0.2143 |
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- | No log | 2.0 | 2 | 0.7154 | 0.5714 |
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- | No log | 3.0 | 3 | 0.5852 | 0.7857 |
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- | No log | 4.0 | 4 | 0.4751 | 0.9286 |
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- | No log | 5.0 | 5 | 0.3943 | 1.0 |
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- | No log | 6.0 | 6 | 0.3377 | 1.0 |
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- | No log | 7.0 | 7 | 0.2968 | 1.0 |
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- | No log | 8.0 | 8 | 0.2719 | 1.0 |
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- | No log | 9.0 | 9 | 0.2576 | 1.0 |
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- | 0.48 | 10.0 | 10 | 0.2522 | 1.0 |
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  ### Framework versions
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- - Transformers 4.41.0
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8403908794788274
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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: 0.4153
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+ - Accuracy: 0.8404
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  ## Model description
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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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+ | 0.5809 | 0.9884 | 64 | 0.5024 | 0.7937 |
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+ | 0.5326 | 1.9923 | 129 | 0.4402 | 0.8132 |
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+ | 0.4626 | 2.9961 | 194 | 0.4244 | 0.8284 |
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+ | 0.4778 | 4.0 | 259 | 0.4234 | 0.8274 |
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+ | 0.4109 | 4.9884 | 323 | 0.4197 | 0.8306 |
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+ | 0.3764 | 5.9923 | 388 | 0.4095 | 0.8295 |
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+ | 0.3725 | 6.9961 | 453 | 0.4046 | 0.8426 |
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+ | 0.3583 | 8.0 | 518 | 0.4109 | 0.8371 |
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+ | 0.3451 | 8.9884 | 582 | 0.4171 | 0.8350 |
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+ | 0.3351 | 9.8842 | 640 | 0.4153 | 0.8404 |
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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  - Tokenizers 0.19.1
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