---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SeizureClassifier_AST_B_43829950
  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. -->

# SeizureClassifier_AST_B_43829950

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0063
- Accuracy: 1.0

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.269         | 0.99  | 44   | 1.1676          | 0.8564   |
| 0.7525        | 1.99  | 88   | 0.5446          | 0.9777   |
| 0.3005        | 2.98  | 132  | 0.2273          | 0.9876   |
| 0.185         | 4.0   | 177  | 0.1556          | 0.9653   |
| 0.0935        | 4.99  | 221  | 0.0798          | 0.9901   |
| 0.0545        | 5.99  | 265  | 0.0313          | 0.9950   |
| 0.0416        | 6.98  | 309  | 0.0278          | 0.9950   |
| 0.0264        | 8.0   | 354  | 0.0682          | 0.9851   |
| 0.0109        | 8.99  | 398  | 0.0311          | 0.9950   |
| 0.0104        | 9.99  | 442  | 0.0085          | 1.0      |
| 0.0083        | 10.98 | 486  | 0.0143          | 0.9975   |
| 0.0067        | 12.0  | 531  | 0.0070          | 1.0      |
| 0.0063        | 12.99 | 575  | 0.0066          | 1.0      |
| 0.006         | 13.99 | 619  | 0.0064          | 1.0      |
| 0.0059        | 14.92 | 660  | 0.0063          | 1.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0