---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- wer
model-index:
- name: working
  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: 0.1690242779130206
---

<!-- 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. -->

# working

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: 0.2700
- Wer: 0.1690

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.2111        | 2.0   | 292  | 0.9069          | 0.5315 |
| 0.6195        | 4.0   | 584  | 0.4762          | 0.3436 |
| 0.4338        | 6.0   | 876  | 0.3627          | 0.2657 |
| 0.3471        | 8.0   | 1168 | 0.4132          | 0.2817 |
| 0.2897        | 10.0  | 1460 | 0.3098          | 0.2178 |
| 0.2471        | 12.0  | 1752 | 0.2761          | 0.1957 |
| 0.2184        | 14.0  | 2044 | 0.2694          | 0.1807 |
| 0.1927        | 16.0  | 2336 | 0.2705          | 0.1753 |
| 0.1754        | 18.0  | 2628 | 0.2692          | 0.1709 |
| 0.1622        | 20.0  | 2920 | 0.2700          | 0.1690 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1