---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- wer
base_model: foxxy-hm/wav2vec2-base-finetune-vi-v6
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 [foxxy-hm/wav2vec2-base-finetune-vi-v6](https://huggingface.co/foxxy-hm/wav2vec2-base-finetune-vi-v6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2240
- Wer: 0.1296

## 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: 6e-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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0848        | 1.18  | 500  | 0.1792          | 0.1299 |
| 0.0881        | 2.37  | 1000 | 0.1978          | 0.1322 |
| 0.0789        | 3.55  | 1500 | 0.2050          | 0.1330 |
| 0.0729        | 4.74  | 2000 | 0.2013          | 0.1320 |
| 0.0611        | 5.92  | 2500 | 0.2034          | 0.1334 |
| 0.0597        | 7.11  | 3000 | 0.2116          | 0.1326 |
| 0.0581        | 8.29  | 3500 | 0.2123          | 0.1323 |
| 0.0481        | 9.48  | 4000 | 0.2134          | 0.1310 |
| 0.0507        | 10.66 | 4500 | 0.2222          | 0.1314 |
| 0.0441        | 11.85 | 5000 | 0.2142          | 0.1312 |
| 0.0427        | 13.03 | 5500 | 0.2270          | 0.1302 |
| 0.0402        | 14.22 | 6000 | 0.2212          | 0.1298 |
| 0.0402        | 15.4  | 6500 | 0.2150          | 0.1288 |
| 0.0381        | 16.59 | 7000 | 0.2240          | 0.1294 |
| 0.039         | 17.77 | 7500 | 0.2224          | 0.1286 |
| 0.0383        | 18.96 | 8000 | 0.2240          | 0.1296 |


### Framework versions

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