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_43243531
  results: []
---

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# SeizureClassifier_Wav2Vec_43243531

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: 0.0063
- Accuracy: 0.9990

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.13          | 1.0   | 339  | 0.1382          | 0.9616   |
| 0.0931        | 2.0   | 678  | 0.0613          | 0.9839   |
| 0.0265        | 3.0   | 1017 | 0.0248          | 0.9942   |
| 0.026         | 4.0   | 1357 | 0.0612          | 0.9900   |
| 0.0252        | 5.0   | 1696 | 0.0460          | 0.9894   |
| 0.0369        | 6.0   | 2035 | 0.0148          | 0.9968   |
| 0.0018        | 7.0   | 2374 | 0.0049          | 0.9990   |
| 0.0007        | 8.0   | 2714 | 0.0114          | 0.9981   |
| 0.0056        | 9.0   | 3053 | 0.0107          | 0.9987   |
| 0.0003        | 10.0  | 3392 | 0.0067          | 0.9990   |
| 0.0101        | 11.0  | 3731 | 0.0039          | 0.9994   |
| 0.0073        | 12.0  | 4071 | 0.0049          | 0.9994   |
| 0.0113        | 13.0  | 4410 | 0.0061          | 0.9990   |
| 0.0002        | 14.0  | 4749 | 0.0067          | 0.9990   |
| 0.0002        | 14.99 | 5085 | 0.0063          | 0.9990   |


### Framework versions

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