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finetuned-parkinson-classification
skohli01/finetuned-parkinson-classification
finetuned-parkinson-classification is a image classification model from skohli01. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
swin-tiny-patch4-window7-224-finetuned-parkinson-classification
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4110
- Accuracy: 0.9091
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.8891 | 0.3636 |
| No log | 2.0 | 3 | 0.5901 | 0.6364 |
| No log | 3.0 | 5 | 0.5270 | 0.6364 |
| No log | 4.0 | 6 | 0.4946 | 0.7273 |
| No log | 5.0 | 7 | 0.4724 | 0.8182 |
| No log | 6.0 | 9 | 0.4406 | 0.8182 |
| 0.3043 | 7.0 | 11 | 0.4110 | 0.9091 |
| 0.3043 | 8.0 | 12 | 0.4048 | 0.9091 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- License
- apache-2.0
- Created
- Nov 26, 2024
- Updated
- Nov 26, 2024