---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-finetune-vi-v5
  results: []
---

<!-- 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-base-finetune-vi-v5

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-large-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-large-vi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2373
- Wer: 0.1681

## 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: 5e-05
- train_batch_size: 16
- 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 20.4793       | 0.99  | 500   | 8.0023          | 1.0    |
| 4.5661        | 1.98  | 1000  | 3.4221          | 1.0    |
| 3.356         | 2.96  | 1500  | 3.2739          | 1.0    |
| 2.2533        | 3.95  | 2000  | 0.8992          | 0.4884 |
| 0.8412        | 4.94  | 2500  | 0.5181          | 0.3061 |
| 0.5738        | 5.93  | 3000  | 0.3986          | 0.2586 |
| 0.4608        | 6.92  | 3500  | 0.3545          | 0.2230 |
| 0.399         | 7.91  | 4000  | 0.3220          | 0.2003 |
| 0.341         | 8.89  | 4500  | 0.2936          | 0.1928 |
| 0.3094        | 9.88  | 5000  | 0.2727          | 0.1873 |
| 0.2834        | 10.87 | 5500  | 0.2721          | 0.1813 |
| 0.2761        | 11.86 | 6000  | 0.2704          | 0.1817 |
| 0.2505        | 12.85 | 6500  | 0.2597          | 0.1766 |
| 0.2472        | 13.83 | 7000  | 0.2460          | 0.1744 |
| 0.2335        | 14.82 | 7500  | 0.2486          | 0.1728 |
| 0.2183        | 15.81 | 8000  | 0.2430          | 0.1714 |
| 0.2153        | 16.8  | 8500  | 0.2433          | 0.1697 |
| 0.2029        | 17.79 | 9000  | 0.2408          | 0.1688 |
| 0.2094        | 18.77 | 9500  | 0.2349          | 0.1694 |
| 0.2045        | 19.76 | 10000 | 0.2373          | 0.1681 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.8.0
- Tokenizers 0.13.3