---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: wav2vec2-base-finetuned-common_voice
  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. -->

# wav2vec2-base-finetuned-common_voice

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: 0.0560
- Accuracy: 0.99
- F1: 0.9900
- Recall: 0.99
- Precision: 0.9902
- Mcc: 0.9875
- Auc: 0.9983

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision | Mcc    | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.7394        | 1.0   | 200  | 0.2528          | 0.95     | 0.9497 | 0.95   | 0.9554    | 0.9390 | 0.9952 |
| 0.0013        | 2.0   | 400  | 0.0069          | 0.9975   | 0.9975 | 0.9975 | 0.9975    | 0.9969 | 1.0    |
| 0.0435        | 3.0   | 600  | 0.0962          | 0.985    | 0.9850 | 0.9850 | 0.9852    | 0.9813 | 0.9987 |
| 0.1172        | 4.0   | 800  | 0.0434          | 0.995    | 0.9950 | 0.9950 | 0.9950    | 0.9938 | 0.9993 |
| 0.0005        | 5.0   | 1000 | 0.0496          | 0.9925   | 0.9925 | 0.9925 | 0.9926    | 0.9906 | 0.9984 |
| 0.0006        | 6.0   | 1200 | 0.0652          | 0.99     | 0.9900 | 0.99   | 0.9901    | 0.9875 | 0.9991 |
| 0.0004        | 7.0   | 1400 | 0.0267          | 0.9975   | 0.9975 | 0.9975 | 0.9975    | 0.9969 | 0.9982 |
| 0.0003        | 8.0   | 1600 | 0.0423          | 0.9925   | 0.9925 | 0.9925 | 0.9926    | 0.9906 | 0.9982 |
| 0.0003        | 9.0   | 1800 | 0.0549          | 0.9875   | 0.9875 | 0.9875 | 0.9877    | 0.9844 | 0.9982 |
| 0.0003        | 10.0  | 2000 | 0.0560          | 0.99     | 0.9900 | 0.99   | 0.9902    | 0.9875 | 0.9983 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1