---
library_name: transformers
license: cc-by-nc-4.0
base_model: nguyenvulebinh/wav2vec2-base-vi
tags:
- generated_from_trainer
datasets:
- doof-ferb/LSVSC
metrics:
- f1
model-index:
- name: vietnamese-regional-voice-classification-model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: LSVSC
      type: doof-ferb/LSVSC
    metrics:
    - name: F1
      type: f1
      value: 0.7852888029210245
---

<!-- 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. -->

# vietnamese-regional-voice-classification-model

This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the LSVSC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6087
- F1: 0.7853

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.0733        | 1.0   | 44   | 0.8828          | 0.7566 |
| 0.8621        | 2.0   | 88   | 0.7323          | 0.7653 |
| 0.7834        | 3.0   | 132  | 0.6746          | 0.7992 |
| 0.7098        | 4.0   | 176  | 0.8050          | 0.6410 |
| 0.6748        | 5.0   | 220  | 0.7053          | 0.7113 |
| 0.6335        | 6.0   | 264  | 0.6650          | 0.7491 |
| 0.6195        | 7.0   | 308  | 0.6096          | 0.7742 |
| 0.6118        | 8.0   | 352  | 0.6087          | 0.7853 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0