---
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: 0.0870
- Accuracy: 0.9875
- F1: 0.9875
- Recall: 0.9875
- Precision: 0.9877
- Mcc: 0.9844
- Auc: 0.9968

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.9826        | 1.0   | 200  | 0.9330          | 0.715    | 0.6769 | 0.7150 | 0.7516    | 0.6708 | 0.9379 |
| 0.2818        | 2.0   | 400  | 0.5294          | 0.8425   | 0.8362 | 0.8425 | 0.8731    | 0.8133 | 0.9738 |
| 0.1229        | 3.0   | 600  | 0.2185          | 0.945    | 0.9455 | 0.945  | 0.9476    | 0.9317 | 0.9917 |
| 0.0094        | 4.0   | 800  | 0.2905          | 0.9425   | 0.9428 | 0.9425 | 0.9476    | 0.9293 | 0.9932 |
| 0.0256        | 5.0   | 1000 | 0.1565          | 0.97     | 0.9702 | 0.97   | 0.9720    | 0.9629 | 0.9972 |
| 0.0032        | 6.0   | 1200 | 0.1577          | 0.9775   | 0.9775 | 0.9775 | 0.9778    | 0.9720 | 0.9941 |
| 0.0869        | 7.0   | 1400 | 0.1017          | 0.9825   | 0.9824 | 0.9825 | 0.9826    | 0.9782 | 0.9965 |
| 0.0019        | 8.0   | 1600 | 0.1194          | 0.9775   | 0.9776 | 0.9775 | 0.9783    | 0.9720 | 0.9967 |
| 0.0017        | 9.0   | 1800 | 0.0947          | 0.985    | 0.9850 | 0.9850 | 0.9851    | 0.9813 | 0.9972 |
| 0.0016        | 10.0  | 2000 | 0.0870          | 0.9875   | 0.9875 | 0.9875 | 0.9877    | 0.9844 | 0.9968 |


### Framework versions

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