---
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: 0.0419
- Accuracy: 0.995
- F1: 0.9950
- Recall: 0.9950
- Precision: 0.9951
- Mcc: 0.9938
- Auc: 0.9987

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.8258        | 1.0   | 200  | 0.7423          | 0.76     | 0.6973 | 0.76   | 0.6699    | 0.7402 | 0.9766 |
| 0.1609        | 2.0   | 400  | 0.1559          | 0.96     | 0.9596 | 0.96   | 0.9644    | 0.9513 | 0.9997 |
| 0.219         | 3.0   | 600  | 0.0864          | 0.9825   | 0.9826 | 0.9825 | 0.9828    | 0.9782 | 0.9983 |
| 0.0049        | 4.0   | 800  | 0.0341          | 0.995    | 0.9950 | 0.9950 | 0.9950    | 0.9938 | 0.9999 |
| 0.0031        | 5.0   | 1000 | 0.1241          | 0.98     | 0.9799 | 0.9800 | 0.9808    | 0.9752 | 0.9989 |
| 0.0021        | 6.0   | 1200 | 0.0394          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9988 |
| 0.0017        | 7.0   | 1400 | 0.0410          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9993 |
| 0.0015        | 8.0   | 1600 | 0.0420          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |
| 0.0013        | 9.0   | 1800 | 0.0418          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |
| 0.0013        | 10.0  | 2000 | 0.0419          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1