---
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: 0.46064565231179044
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/khackho01125-CMC-University/Wav2Vec2/runs/3iat438k)
# 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: 0.8301
- Wer: 0.4606

## 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: 400
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.7906        | 2.0   | 292  | 3.6543          | 1.0    |
| 3.4396        | 4.0   | 584  | 3.5033          | 1.0    |
| 3.4081        | 6.0   | 876  | 3.4360          | 1.0    |
| 2.4196        | 8.0   | 1168 | 1.5751          | 0.8002 |
| 1.3285        | 10.0  | 1460 | 1.1699          | 0.6628 |
| 1.0944        | 12.0  | 1752 | 1.0408          | 0.6051 |
| 0.9742        | 14.0  | 2044 | 0.9772          | 0.5657 |
| 0.9219        | 16.0  | 2336 | 0.9344          | 0.5515 |
| 0.817         | 18.0  | 2628 | 0.8871          | 0.5176 |
| 0.7636        | 20.0  | 2920 | 0.8734          | 0.5050 |
| 0.7192        | 22.0  | 3212 | 0.8556          | 0.4909 |
| 0.6904        | 24.0  | 3504 | 0.8471          | 0.4772 |
| 0.6703        | 26.0  | 3796 | 0.8489          | 0.4754 |
| 0.6343        | 28.0  | 4088 | 0.8364          | 0.4689 |
| 0.6161        | 30.0  | 4380 | 0.8301          | 0.4606 |


### Framework versions

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