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

Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results
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  1. README.md +15 -14
  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: 0.3924731182795699
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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: 2.0567
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- - Accuracy: 0.3925
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | No log | 0.8889 | 6 | 2.8975 | 0.1398 |
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- | 2.9658 | 1.9259 | 13 | 2.6866 | 0.2204 |
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- | 2.6529 | 2.9630 | 20 | 2.4370 | 0.3011 |
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- | 2.6529 | 4.0 | 27 | 2.2516 | 0.3495 |
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- | 2.3311 | 4.8889 | 33 | 2.1685 | 0.3710 |
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- | 2.1441 | 5.9259 | 40 | 2.0987 | 0.3656 |
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- | 2.1441 | 6.9630 | 47 | 2.0567 | 0.3925 |
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- | 2.0507 | 8.0 | 54 | 2.0416 | 0.3871 |
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- | 1.988 | 8.8889 | 60 | 2.0368 | 0.3763 |
 
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  ### Framework versions
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- - Transformers 4.41.2
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- - Pytorch 1.13.1+cu117
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  - Datasets 2.19.2
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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: 0.8807785888077859
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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: 0.2599
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+ - Accuracy: 0.8808
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.4494 | 0.9836 | 30 | 0.4953 | 0.8224 |
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+ | 0.3369 | 2.0 | 61 | 0.3206 | 0.8832 |
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+ | 0.3173 | 2.9836 | 91 | 0.3023 | 0.8735 |
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+ | 0.2865 | 4.0 | 122 | 0.2900 | 0.8735 |
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+ | 0.2612 | 4.9836 | 152 | 0.2862 | 0.8710 |
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+ | 0.2412 | 6.0 | 183 | 0.2637 | 0.8856 |
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+ | 0.2533 | 6.9836 | 213 | 0.2769 | 0.8783 |
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+ | 0.2413 | 8.0 | 244 | 0.2649 | 0.8832 |
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+ | 0.2139 | 8.9836 | 274 | 0.2633 | 0.8783 |
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+ | 0.2087 | 9.8361 | 300 | 0.2599 | 0.8808 |
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  ### Framework versions
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+ - Transformers 4.42.3
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+ - Pytorch 1.12.1+cu113
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  - Datasets 2.19.2
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  - Tokenizers 0.19.1
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