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swin-tiny-patch4-window7-224-finetuned-parkinson-classification

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VasundharaBoomi commited on
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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Apr16_07-56-15_bdf997e550a6/events.out.tfevents.1713254199.bdf997e550a6.402.0 +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: 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: 0.3967
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- - Accuracy: 1.0
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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 | 1.0 | 1 | 0.7001 | 0.4545 |
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- | No log | 2.0 | 3 | 0.6141 | 0.7273 |
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- | No log | 3.0 | 5 | 0.5465 | 0.7273 |
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- | No log | 4.0 | 6 | 0.4669 | 0.9091 |
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- | No log | 5.0 | 7 | 0.4453 | 0.7273 |
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- | No log | 6.0 | 9 | 0.4054 | 0.9091 |
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- | 0.2807 | 7.0 | 11 | 0.3967 | 1.0 |
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- | 0.2807 | 8.0 | 12 | 0.3939 | 1.0 |
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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: 0.9090909090909091
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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: 0.3166
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+ - Accuracy: 0.9091
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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 | 1.0 | 1 | 0.6990 | 0.7273 |
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+ | No log | 2.0 | 3 | 0.5095 | 0.8182 |
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+ | No log | 3.0 | 5 | 0.4284 | 0.9091 |
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+ | No log | 4.0 | 6 | 0.4101 | 0.9091 |
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+ | No log | 5.0 | 7 | 0.3774 | 0.9091 |
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+ | No log | 6.0 | 9 | 0.3373 | 0.9091 |
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+ | 0.2942 | 7.0 | 11 | 0.3182 | 0.9091 |
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+ | 0.2942 | 8.0 | 12 | 0.3166 | 0.9091 |
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  ### Framework versions
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