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seizure_vit_jlb_231126_ff_raw_combo_multichannel
JLB-JLB/seizure_vit_jlb_231126_ff_raw_combo_multichannel
seizure_vit_jlb_231126_ff_raw_combo_multichannel 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 26, 2023
- Updated
- Nov 26, 2023
- SHA
- f31b7d2c
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_231126_ff_raw_combo_multichannel
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the JLB-JLB/seizure_detection_224x224_raw_freq_combo_multichannel dataset. It achieves the following results on the evaluation set:
- Loss: 0.6323
- Roc Auc: 0.7311
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc |
|---|---|---|---|---|
| 0.3219 | 0.17 | 1000 | 0.6337 | 0.7311 |
| 0.3625 | 0.34 | 2000 | 0.6381 | 0.7038 |
| 0.3435 | 0.51 | 3000 | 0.6890 | 0.7010 |
| 0.2538 | 0.68 | 4000 | 0.7449 | 0.6927 |
| 0.2545 | 0.85 | 5000 | 0.7448 | 0.7049 |
| 0.1387 | 1.02 | 6000 | 1.0363 | 0.7127 |
| 0.1765 | 1.19 | 7000 | 0.8541 | 0.7223 |
| 0.1385 | 1.36 | 8000 | 1.0059 | 0.7228 |
| 0.1602 | 1.53 | 9000 | 0.8951 | 0.7070 |
| 0.1158 | 1.7 | 10000 | 1.0356 | 0.7220 |
| 0.0973 | 1.87 | 11000 | 1.0616 | 0.7132 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Nov 26, 2023
- Updated
- Nov 26, 2023