---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- wer
model-index:
- name: wav2vec2-vivos-asr
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: vivos
      type: vivos
      config: default
      split: None
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.239169022417987
---

<!-- 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-asr

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: 0.3501
- Wer: 0.2392

## 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: 8e-05
- 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.7262        | 2.0   | 146  | 5.1186          | 1.0    |
| 3.6815        | 4.0   | 292  | 3.6847          | 1.0    |
| 3.4316        | 6.0   | 438  | 3.5415          | 1.0    |
| 2.8102        | 8.0   | 584  | 1.5866          | 0.9160 |
| 0.8818        | 10.0  | 730  | 0.5903          | 0.4066 |
| 0.4305        | 12.0  | 876  | 0.4283          | 0.3104 |
| 0.3067        | 14.0  | 1022 | 0.3793          | 0.2762 |
| 0.2819        | 16.0  | 1168 | 0.3620          | 0.2496 |
| 0.2235        | 18.0  | 1314 | 0.3507          | 0.2405 |
| 0.211         | 20.0  | 1460 | 0.3501          | 0.2392 |


### Framework versions

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