---
language:
- vi
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- wer
model-index:
- name: Whisper Base Vi - Duy Ta
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Vivos
      type: vivos
      config: clean vivos
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 25.058275058275058
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Vi - DuyTa

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Vivos dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2565
- Wer: 25.0583

## Model description

Finetune Whisper model on Vietnamese Dataset

## Intended uses & limitations

More information needed

## Training and evaluation data

Vivos

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-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: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2096        | 1.37  | 1000 | 0.2949          | 32.0383 |
| 0.1205        | 2.74  | 2000 | 0.2548          | 26.8583 |
| 0.0767        | 4.12  | 3000 | 0.2549          | 25.3432 |
| 0.0532        | 5.49  | 4000 | 0.2565          | 25.0583 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3