---
license: cc-by-nc-4.0
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: model_weight_with_token_110_11
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: vi
      split: None
      args: vi
    metrics:
    - name: Wer
      type: wer
      value: 0.1738111185532485
---

<!-- 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. -->

# model_weight_with_token_110_11

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0692
- Cer: 0.0582
- Wer: 0.1738

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Cer    | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 0.5359        | 1.3928  | 500   | 0.1281          | 0.0733 | 0.2101 |
| 0.4994        | 2.7855  | 1000  | 0.1591          | 0.0731 | 0.2098 |
| 0.4735        | 4.1783  | 1500  | 0.1169          | 0.0708 | 0.2022 |
| 0.4432        | 5.5710  | 2000  | 0.1102          | 0.0710 | 0.2031 |
| 0.4204        | 6.9638  | 2500  | 0.1127          | 0.0735 | 0.2023 |
| 0.3919        | 8.3565  | 3000  | 0.1146          | 0.0699 | 0.1992 |
| 0.3701        | 9.7493  | 3500  | 0.1047          | 0.0712 | 0.1993 |
| 0.3826        | 11.1421 | 4000  | 0.1073          | 0.0688 | 0.1952 |
| 0.3512        | 12.5348 | 4500  | 0.0898          | 0.0650 | 0.1894 |
| 0.327         | 13.9276 | 5000  | 0.0931          | 0.0650 | 0.1869 |
| 0.3284        | 15.3203 | 5500  | 0.1028          | 0.0672 | 0.1918 |
| 0.3016        | 16.7131 | 6000  | 0.0973          | 0.0651 | 0.1875 |
| 0.2893        | 18.1058 | 6500  | 0.0899          | 0.0638 | 0.1849 |
| 0.292         | 19.4986 | 7000  | 0.0882          | 0.0632 | 0.1840 |
| 0.2688        | 20.8914 | 7500  | 0.0808          | 0.0625 | 0.1820 |
| 0.2672        | 22.2841 | 8000  | 0.0807          | 0.0620 | 0.1818 |
| 0.266         | 23.6769 | 8500  | 0.0807          | 0.0621 | 0.1816 |
| 0.2499        | 25.0696 | 9000  | 0.0741          | 0.0615 | 0.1787 |
| 0.244         | 26.4624 | 9500  | 0.0780          | 0.0620 | 0.1803 |
| 0.2403        | 27.8552 | 10000 | 0.0764          | 0.0607 | 0.1791 |
| 0.2268        | 29.2479 | 10500 | 0.0750          | 0.0599 | 0.1778 |
| 0.2318        | 30.6407 | 11000 | 0.0728          | 0.0600 | 0.1775 |
| 0.2143        | 32.0334 | 11500 | 0.0723          | 0.0592 | 0.1757 |
| 0.2193        | 33.4262 | 12000 | 0.0699          | 0.0591 | 0.1749 |
| 0.1992        | 34.8189 | 12500 | 0.0717          | 0.0585 | 0.1748 |
| 0.2238        | 36.2117 | 13000 | 0.0692          | 0.0587 | 0.1744 |
| 0.2074        | 37.6045 | 13500 | 0.0696          | 0.0581 | 0.1735 |
| 0.1984        | 38.9972 | 14000 | 0.0692          | 0.0582 | 0.1738 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1