---
base_model: facebook/wav2vec2-base
datasets:
- common_voice_13_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-vi-colab
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: vi
      split: test[:50%]
      args: vi
    metrics:
    - type: wer
      value: 1.0
      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-large-xls-r-vi-colab

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4884
- Wer: 1.0
- Cer: 1.0

## 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: 1e-05
- 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: 0.1
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:---:|:---:|
| 9.4752        | 7.1111  | 160  | 4.4992          | 1.0 | 1.0 |
| 4.2035        | 14.2222 | 320  | 3.9228          | 1.0 | 1.0 |
| 3.7611        | 21.3333 | 480  | 3.6584          | 1.0 | 1.0 |
| 3.5825        | 28.4444 | 640  | 3.5584          | 1.0 | 1.0 |
| 3.5044        | 35.5556 | 800  | 3.5285          | 1.0 | 1.0 |
| 3.4669        | 42.6667 | 960  | 3.5226          | 1.0 | 1.0 |
| 3.4382        | 49.7778 | 1120 | 3.5093          | 1.0 | 1.0 |
| 3.4183        | 56.8889 | 1280 | 3.4942          | 1.0 | 1.0 |
| 3.4002        | 64.0    | 1440 | 3.4957          | 1.0 | 1.0 |
| 3.3871        | 71.1111 | 1600 | 3.4896          | 1.0 | 1.0 |
| 3.382         | 78.2222 | 1760 | 3.4884          | 1.0 | 1.0 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1