shivarama23
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update model card README.md
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 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
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@@ -29,8 +29,8 @@ 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 image_folder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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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:
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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.
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| No log | 2.0 | 2 | 0.
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| No log | 3.0 | 3 | 0.
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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: 0.8181818181818182
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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 image_folder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4992
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- Accuracy: 0.8182
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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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| No log | 1.0 | 1 | 0.6762 | 0.6364 |
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| No log | 2.0 | 2 | 0.6309 | 0.7273 |
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| No log | 3.0 | 3 | 0.6095 | 0.6364 |
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| No log | 4.0 | 4 | 0.5775 | 0.6364 |
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| No log | 5.0 | 5 | 0.5443 | 0.8182 |
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| No log | 6.0 | 6 | 0.5242 | 0.9091 |
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| No log | 7.0 | 7 | 0.5149 | 0.8182 |
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| No log | 8.0 | 8 | 0.5094 | 0.8182 |
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| No log | 9.0 | 9 | 0.5038 | 0.8182 |
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| 0.4095 | 10.0 | 10 | 0.4992 | 0.8182 |
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### Framework versions
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