---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: wav2vec2-common-voice-16_1_vi
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_16_1
      type: common_voice_16_1
      config: vi
      split: None
      args: vi
    metrics:
    - type: wer
      value: 0.8006303375355835
      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-16_1_vi

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4738
- Wer: 0.8006

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 17.2554       | 4.24  | 500  | 3.5535          | 1.0    |
| 3.4431        | 8.47  | 1000 | 3.3988          | 1.0    |
| 2.4492        | 12.71 | 1500 | 1.7446          | 1.0539 |
| 0.9214        | 16.95 | 2000 | 1.4497          | 0.8814 |
| 0.5148        | 21.19 | 2500 | 1.4543          | 0.8333 |
| 0.3619        | 25.42 | 3000 | 1.4791          | 0.8121 |
| 0.3003        | 29.66 | 3500 | 1.4738          | 0.8006 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2