---
base_model: facebook/wav2vec2-base
datasets:
- vivos
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-vivos
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: vivos
      type: vivos
      config: default
      split: None
      args: default
    metrics:
    - type: wer
      value: 0.23636599442318915
      name: Wer
---

<!-- 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-vivos

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4755
- Wer: 0.2364

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.349         | 2.0   | 146  | 0.9904          | 0.6088 |
| 0.718         | 4.0   | 292  | 0.6959          | 0.4630 |
| 0.4692        | 6.0   | 438  | 0.5304          | 0.3414 |
| 0.3385        | 8.0   | 584  | 0.5078          | 0.3216 |
| 0.2627        | 10.0  | 730  | 0.4659          | 0.2788 |
| 0.2033        | 12.0  | 876  | 0.4751          | 0.2656 |
| 0.1699        | 14.0  | 1022 | 0.4659          | 0.2519 |
| 0.1688        | 16.0  | 1168 | 0.4662          | 0.2394 |
| 0.1269        | 18.0  | 1314 | 0.4707          | 0.2375 |
| 0.1162        | 20.0  | 1460 | 0.4755          | 0.2364 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1