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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-finetuned-parkinson-classification |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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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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should probably proofread and complete it, then remove this comment. --> |
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# swin-tiny-patch4-window7-224-finetuned-parkinson-classification |
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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: 0.4966 |
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- Accuracy: 0.9091 |
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## Model description |
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This model was created by importing the dataset of spiral drawings made by both parkinsons patients and healthy people into Google Colab from kaggle here: https://www.kaggle.com/datasets/kmader/parkinsons-drawings/data. I then used the image classification tutorial here: https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb |
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obtaining the following notebook: |
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https://colab.research.google.com/drive/1oRjwgHjmaQYRU1qf-TTV7cg1qMZXgMaO?usp=sharing |
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The possible classified data are: |
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<ul> |
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<li>Healthy</li> |
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<li>Parkinson</li> |
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</ul> |
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### Spiral drawing example: |
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## Intended uses & limitations |
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Acknowledgements |
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The data came from the paper: Zham P, Kumar DK, Dabnichki P, Poosapadi Arjunan S and Raghav S (2017) Distinguishing Different Stages of Parkinson’s Disease Using Composite Index of Speed and Pen-Pressure of Sketching a Spiral. Front. Neurol. 8:435. doi: 10.3389/fneur.2017.00435 |
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https://www.frontiersin.org/articles/10.3389/fneur.2017.00435/full |
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Data licence : https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 20 |
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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 | 0.6801 | 0.4545 | |
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| No log | 2.0 | 3 | 0.8005 | 0.3636 | |
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| No log | 3.0 | 5 | 0.6325 | 0.6364 | |
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| No log | 4.0 | 6 | 0.5494 | 0.8182 | |
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| No log | 5.0 | 7 | 0.5214 | 0.8182 | |
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| No log | 6.0 | 9 | 0.5735 | 0.7273 | |
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| 0.3063 | 7.0 | 11 | 0.4966 | 0.9091 | |
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| 0.3063 | 8.0 | 12 | 0.4557 | 0.9091 | |
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| 0.3063 | 9.0 | 13 | 0.4444 | 0.9091 | |
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| 0.3063 | 10.0 | 15 | 0.6226 | 0.6364 | |
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| 0.3063 | 11.0 | 17 | 0.8224 | 0.4545 | |
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| 0.3063 | 12.0 | 18 | 0.8127 | 0.4545 | |
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| 0.3063 | 13.0 | 19 | 0.7868 | 0.4545 | |
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| 0.2277 | 14.0 | 21 | 0.8195 | 0.4545 | |
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| 0.2277 | 15.0 | 23 | 0.7499 | 0.4545 | |
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| 0.2277 | 16.0 | 24 | 0.7022 | 0.5455 | |
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| 0.2277 | 17.0 | 25 | 0.6755 | 0.5455 | |
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| 0.2277 | 18.0 | 27 | 0.6277 | 0.6364 | |
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| 0.2277 | 19.0 | 29 | 0.5820 | 0.6364 | |
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| 0.1867 | 20.0 | 30 | 0.5784 | 0.6364 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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