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update model card README.md

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  1. README.md +11 -10
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@@ -7,8 +7,6 @@ metrics:
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  model-index:
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  - name: test_triage
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  results: []
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- datasets:
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- - arunboss/test
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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
@@ -16,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # test_triage
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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 Test dataset (I plan to make it bigger and more neater soon for others to build on).
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  It achieves the following results on the evaluation set:
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- - Loss: 2.5160
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- - Accuracy: 0.3900
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  ## Model description
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@@ -47,15 +45,18 @@ 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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- | 3.3151 | 1.0 | 151 | 3.2356 | 0.2498 |
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- | 2.7912 | 2.0 | 303 | 2.6766 | 0.3433 |
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- | 2.67 | 2.99 | 453 | 2.5160 | 0.3900 |
 
 
 
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  ### Framework versions
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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  model-index:
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  - name: test_triage
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  results: []
 
 
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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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  # test_triage
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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 None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9758
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+ - Accuracy: 0.5008
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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: 6
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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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+ | 3.3471 | 1.0 | 151 | 3.2152 | 0.2452 |
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+ | 2.7313 | 2.0 | 303 | 2.5291 | 0.3817 |
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+ | 2.48 | 3.0 | 454 | 2.2459 | 0.4413 |
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+ | 2.2192 | 4.0 | 606 | 2.0968 | 0.4702 |
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+ | 2.0479 | 5.0 | 757 | 2.0026 | 0.4897 |
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+ | 1.9702 | 5.98 | 906 | 1.9758 | 0.5008 |
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  ### Framework versions
 
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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+ - Tokenizers 0.13.3