---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
model-index:
- name: result_weight
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: vi
      split: None
      args: vi
    metrics:
    - type: wer
      value: 0.7862032648762507
      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. -->

# result_weight

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6430
- Wer: 0.7862

## 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: 32
- 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 19.1789       | 6.3291  | 500  | 5.0724          | 1.0    |
| 4.4582        | 12.6582 | 1000 | 3.4558          | 0.9989 |
| 3.8596        | 18.9873 | 1500 | 3.1687          | 0.9905 |
| 2.8095        | 25.3165 | 2000 | 2.2626          | 0.9084 |
| 2.0404        | 31.6456 | 2500 | 1.8938          | 0.8220 |
| 1.6879        | 37.9747 | 3000 | 1.6430          | 0.7862 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1