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# seizure_vit_jlb_231027

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the JLB-JLB/seizure_eeg_greyscale_224x224_6secWindow_adjusted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4759
- Roc Auc: 0.7822

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.4787        | 0.17  | 1000  | 0.5094          | 0.7706  |
| 0.3695        | 0.34  | 2000  | 0.5111          | 0.7359  |
| 0.337         | 0.51  | 3000  | 0.4734          | 0.7829  |
| 0.3604        | 0.68  | 4000  | 0.5508          | 0.7457  |
| 0.3222        | 0.85  | 5000  | 0.5817          | 0.7687  |
| 0.2315        | 1.02  | 6000  | 0.6515          | 0.7679  |
| 0.2388        | 1.19  | 7000  | 0.5681          | 0.7543  |
| 0.2691        | 1.36  | 8000  | 0.5307          | 0.7691  |
| 0.268         | 1.53  | 9000  | 0.5643          | 0.7610  |
| 0.131         | 1.7   | 10000 | 0.7293          | 0.7451  |
| 0.2303        | 1.87  | 11000 | 0.6291          | 0.7704  |
| 0.1442        | 2.04  | 12000 | 0.6372          | 0.7871  |
| 0.1325        | 2.21  | 13000 | 0.8672          | 0.7319  |
| 0.1986        | 2.38  | 14000 | 0.7352          | 0.7532  |
| 0.1669        | 2.55  | 15000 | 0.8195          | 0.7562  |
| 0.1228        | 2.72  | 16000 | 1.0106          | 0.7239  |
| 0.1071        | 2.89  | 17000 | 0.8957          | 0.7463  |
| 0.1322        | 3.06  | 18000 | 1.0871          | 0.7408  |
| 0.1676        | 3.24  | 19000 | 0.9173          | 0.7683  |
| 0.1105        | 3.41  | 20000 | 1.0175          | 0.7700  |
| 0.1451        | 3.58  | 21000 | 0.9357          | 0.7404  |
| 0.082         | 3.75  | 22000 | 1.1246          | 0.7404  |
| 0.1457        | 3.92  | 23000 | 1.0082          | 0.7502  |
| 0.0336        | 4.09  | 24000 | 1.3685          | 0.7443  |
| 0.0742        | 4.26  | 25000 | 1.5080          | 0.7227  |
| 0.0353        | 4.43  | 26000 | 1.3573          | 0.7421  |
| 0.0557        | 4.6   | 27000 | 1.2484          | 0.7472  |
| 0.075         | 4.77  | 28000 | 1.2750          | 0.7462  |
| 0.0569        | 4.94  | 29000 | 1.3954          | 0.7355  |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

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