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seizure_vit_jlb_231108_iir_adjusted
JLB-JLB/seizure_vit_jlb_231108_iir_adjusted
seizure_vit_jlb_231108_iir_adjusted 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 8, 2023
- Updated
- Nov 9, 2023
- SHA
- 2b902038
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_231108_iir_adjusted
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the JLB-JLB/seizure_eeg_iirFilter_greyscale_224x224_6secWindow_adjusted dataset. It achieves the following results on the evaluation set:
- Loss: 0.4198
- Roc Auc: 0.7773
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: 1e-05
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|---|---|---|---|---|
| 0.3803 | 0.34 | 1000 | 0.4734 | 0.7746 |
| 0.3456 | 0.68 | 2000 | 0.4863 | 0.7782 |
| 0.2831 | 1.02 | 3000 | 0.4817 | 0.7897 |
| 0.2781 | 1.36 | 4000 | 0.5418 | 0.7656 |
| 0.2355 | 1.7 | 5000 | 0.5398 | 0.7786 |
| 0.1978 | 2.04 | 6000 | 0.6121 | 0.7649 |
| 0.149 | 2.38 | 7000 | 0.6402 | 0.7706 |
| 0.1766 | 2.72 | 8000 | 0.6768 | 0.7610 |
| 0.1496 | 3.06 | 9000 | 0.6239 | 0.7733 |
| 0.155 | 3.4 | 10000 | 0.7333 | 0.7602 |
| 0.1238 | 3.75 | 11000 | 0.6513 | 0.7726 |
| 0.1054 | 4.09 | 12000 | 0.7551 | 0.7667 |
| 0.1076 | 4.43 | 13000 | 0.8132 | 0.7627 |
| 0.1321 | 4.77 | 14000 | 0.8152 | 0.7587 |
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 8, 2023
- Updated
- Nov 9, 2023