transformers safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SeizureClassifier_Wav2Vec_43243498
  results: []
---

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# SeizureClassifier_Wav2Vec_43243498

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0520
- Accuracy: 0.9901

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1121        | 0.99  | 44   | 0.9842          | 0.8144   |
| 0.6303        | 1.99  | 88   | 0.5874          | 0.8861   |
| 0.4605        | 2.98  | 132  | 0.3826          | 0.9406   |
| 0.323         | 4.0   | 177  | 0.2791          | 0.9530   |
| 0.2435        | 4.99  | 221  | 0.3828          | 0.8688   |
| 0.2354        | 5.99  | 265  | 0.1321          | 0.9752   |
| 0.2491        | 6.98  | 309  | 0.1552          | 0.9653   |
| 0.1116        | 8.0   | 354  | 0.1540          | 0.9579   |
| 0.0934        | 8.99  | 398  | 0.1053          | 0.9827   |
| 0.0774        | 9.99  | 442  | 0.1016          | 0.9777   |
| 0.0553        | 10.98 | 486  | 0.1856          | 0.9530   |
| 0.0368        | 12.0  | 531  | 0.1151          | 0.9728   |
| 0.017         | 12.99 | 575  | 0.0516          | 0.9876   |
| 0.0153        | 13.99 | 619  | 0.0540          | 0.9901   |
| 0.0144        | 14.92 | 660  | 0.0520          | 0.9901   |


### Framework versions

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