End of training
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README.md
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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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More information needed
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## Intended uses & limitations
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More information needed
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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: 30
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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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all_results.json
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{
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"epoch": 20.0,
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"eval_accuracy": 0.9090909090909091,
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"eval_loss": 0.4965735673904419,
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"eval_runtime": 0.1375,
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"eval_samples_per_second": 79.993,
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"eval_steps_per_second": 7.272
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}
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eval_results.json
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{
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"epoch": 20.0,
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"eval_accuracy": 0.9090909090909091,
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"eval_loss": 0.4965735673904419,
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"eval_runtime": 0.1375,
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"eval_samples_per_second": 79.993,
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"eval_steps_per_second": 7.272
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}
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model.safetensors
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training_args.bin
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