---
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Small Vienamese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 vi
      type: mozilla-foundation/common_voice_16_0
      config: vi
      split: test
      args: vi
    metrics:
    - name: Wer
      type: wer
      value: 24.56800162634682
---

<!-- 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. -->

# Whisper Small Vienamese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_16_0 vi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6705
- Wer: 24.5680

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0174        | 33.0  | 500  | 0.6207          | 24.6696 |
| 0.0045        | 66.0  | 1000 | 0.6705          | 24.5680 |
| 0.0027        | 99.01 | 1500 | 0.6945          | 25.2795 |
| 0.002         | 133.0 | 2000 | 0.7079          | 26.4790 |
| 0.0018        | 166.0 | 2500 | 0.7127          | 26.3976 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0