---
language:
- lus
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- audio
- automatic-speech-recognition
metrics:
- wer
datasets:
  - andrewbawitlung/MiZonal-v2.0
model-index:
- name: Whisper Large v3 Turbo
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MiZonal v2.0
      type: andrewbawitlung/MiZonal-v2.0
      config: default
      split: train
      args: 'config: lus, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 14.491672880934626
pipeline_tag: automatic-speech-recognition
---
![Mizo Automatic Speech Recognition (ASR) Models v2.0](banner.jpg)

<!-- 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 Large v3 Turbo

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the MiZonal v2.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2560
- Wer: 14.4917

## 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.36          | 0.66  | 500  | 0.3358          | 26.2739 |
| 0.1887        | 1.31  | 1000 | 0.2487          | 20.3331 |
| 0.1663        | 1.97  | 1500 | 0.2124          | 17.9302 |
| 0.1002        | 2.62  | 2000 | 0.2090          | 17.4994 |
| 0.0573        | 3.28  | 2500 | 0.2081          | 16.2068 |
| 0.0547        | 3.93  | 3000 | 0.2140          | 16.0080 |
| 0.0291        | 4.59  | 3500 | 0.2229          | 16.1654 |
| 0.0134        | 5.24  | 4000 | 0.2326          | 15.3782 |
| 0.0138        | 5.9   | 4500 | 0.2297          | 15.1131 |
| 0.0047        | 6.55  | 5000 | 0.2485          | 14.9888 |
| 0.0018        | 7.21  | 5500 | 0.2529          | 14.8645 |
| 0.0014        | 7.86  | 6000 | 0.2560          | 14.4917 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1