---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-common-voice-17_0_vi
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: vi
      split: None
      args: vi
    metrics:
    - type: wer
      value: 0.43487928843710294
      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-common-voice-17_0_vi

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_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7992
- Wer: 0.4349

## 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: 8
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.261         | 4.3103  | 500  | 0.4182          | 0.3492 |
| 0.2061        | 8.6207  | 1000 | 0.5416          | 0.4044 |
| 0.1883        | 12.9310 | 1500 | 0.6796          | 0.4304 |
| 0.1336        | 17.2414 | 2000 | 0.8089          | 0.4378 |
| 0.1257        | 21.5517 | 2500 | 0.8244          | 0.4426 |
| 0.098         | 25.8621 | 3000 | 0.7992          | 0.4349 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1