---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-finetune-vi-v6
  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-v6

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: 0.1796
- Wer: 0.1328

## 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: 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: 22

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.006        | 1.18  | 500  | 3.8945          | 0.9994 |
| 3.4476        | 2.37  | 1000 | 3.3364          | 0.9994 |
| 2.1366        | 3.55  | 1500 | 0.4973          | 0.3117 |
| 0.4721        | 4.74  | 2000 | 0.2702          | 0.1827 |
| 0.288         | 5.92  | 2500 | 0.2183          | 0.1578 |
| 0.2313        | 7.11  | 3000 | 0.2134          | 0.1498 |
| 0.2001        | 8.29  | 3500 | 0.1951          | 0.1448 |
| 0.1673        | 9.48  | 4000 | 0.1923          | 0.1391 |
| 0.1575        | 10.66 | 4500 | 0.1835          | 0.1419 |
| 0.1437        | 11.85 | 5000 | 0.1859          | 0.1382 |
| 0.1293        | 13.03 | 5500 | 0.1936          | 0.1371 |
| 0.121         | 14.22 | 6000 | 0.1915          | 0.1359 |
| 0.1159        | 15.4  | 6500 | 0.1814          | 0.1344 |
| 0.1093        | 16.59 | 7000 | 0.1820          | 0.1342 |
| 0.1015        | 17.77 | 7500 | 0.1789          | 0.1350 |
| 0.097         | 18.96 | 8000 | 0.1881          | 0.1337 |
| 0.093         | 20.14 | 8500 | 0.1841          | 0.1331 |
| 0.0928        | 21.33 | 9000 | 0.1796          | 0.1328 |


### Framework versions

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