---
base_model: openai/whisper-small-v3
datasets:
- mozilla-foundation/common_voice_11_0
language:
- vi
library_name: transformers
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper small vi - Ox
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: vi
      split: test
      args: 'config: vi, split: test'
    metrics:
    - type: wer
      value: 14.738458164272398
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper small vi - Ox

This model is a fine-tuned version of [openai/whisper-small-v3](https://huggingface.co/openai/whisper-small-v3) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2529
- Wer: 14.7385

## 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: 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2196        | 1.3928 | 1000 | 0.3174          | 19.4758 |
| 0.0938        | 2.7855 | 2000 | 0.2513          | 16.0325 |
| 0.014         | 4.1783 | 3000 | 0.2467          | 14.4972 |
| 0.0109        | 5.5710 | 4000 | 0.2529          | 14.7385 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 3.0.2
- Tokenizers 0.20.1