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seizure_vit_jlb_231112_fft_raw_combo
JLB-JLB/seizure_vit_jlb_231112_fft_raw_combo
seizure_vit_jlb_231112_fft_raw_combo is a image classification model from JLB-JLB. 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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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023
- SHA
- d0e7fe33
Base models
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. -->
seizure_vit_jlb_231112_fft_raw_combo
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the JLB-JLB/seizure_detection_224x224_raw_frequency dataset. It achieves the following results on the evaluation set:
- Loss: 0.4822
- Roc Auc: 0.7667
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: 2e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|---|---|---|---|---|
| 0.4777 | 0.17 | 500 | 0.5237 | 0.7455 |
| 0.4469 | 0.34 | 1000 | 0.5114 | 0.7542 |
| 0.4122 | 0.52 | 1500 | 0.5084 | 0.7567 |
| 0.3904 | 0.69 | 2000 | 0.5043 | 0.7611 |
| 0.3619 | 0.86 | 2500 | 0.5283 | 0.7609 |
| 0.3528 | 1.03 | 3000 | 0.5352 | 0.7517 |
| 0.3445 | 1.2 | 3500 | 0.5338 | 0.7572 |
| 0.3221 | 1.37 | 4000 | 0.5388 | 0.7509 |
| 0.3109 | 1.55 | 4500 | 0.5641 | 0.7458 |
| 0.3203 | 1.72 | 5000 | 0.5404 | 0.7574 |
| 0.294 | 1.89 | 5500 | 0.5421 | 0.7564 |
| 0.2964 | 2.06 | 6000 | 0.5582 | 0.7493 |
| 0.292 | 2.23 | 6500 | 0.5513 | 0.7561 |
| 0.2838 | 2.4 | 7000 | 0.5557 | 0.7598 |
| 0.2736 | 2.58 | 7500 | 0.5514 | 0.7606 |
| 0.2922 | 2.75 | 8000 | 0.5503 | 0.7538 |
| 0.2699 | 2.92 | 8500 | 0.5535 | 0.7578 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023