---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- seizure-detection
- generated_from_trainer
model-index:
- name: seizure_vit_jlb_231112_fft_raw_combo
  results: []
---

<!-- 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](https://huggingface.co/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