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---
base_model: /content/drive/MyDrive/Seizure_EEG_Research/ViT_Seizure_Detection
tags:
- image-classification
- generated_from_trainer
datasets:
- arrow
metrics:
- matthews_correlation
model-index:
- name: ViT_Seizure_Detection
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: JLB-JLB/seizure_eeg_greyscale_224x224_6secWindow
type: arrow
config: default
split: test
args: default
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.41096197273922397
---
<!-- 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. -->
# ViT_Seizure_Detection
This model is a fine-tuned version of [/content/drive/MyDrive/Seizure_EEG_Research/ViT_Seizure_Detection](https://huggingface.co//content/drive/MyDrive/Seizure_EEG_Research/ViT_Seizure_Detection) on the JLB-JLB/seizure_eeg_greyscale_224x224_6secWindow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1622
- Matthews Correlation: 0.4110
## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
| 0.0742 | 0.79 | 10000 | 0.2080 | 0.4431 |
| 0.0409 | 1.57 | 20000 | 0.2175 | 0.4470 |
| 0.0345 | 2.36 | 30000 | 0.2514 | 0.4717 |
| 0.0184 | 3.14 | 40000 | 0.3040 | 0.4261 |
| 0.0092 | 3.93 | 50000 | 0.3495 | 0.4389 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|