---
language:
- lus
license: apache-2.0
pipeline_tag: automatic-speech-recognition
base_model: openai/whisper-small
tags:
- audio
- automatic-speech-recognition
datasets:
- andrewbawitlung/MiZonal-v2.0
metrics:
- wer
model-index:
- name: Whisper Small
  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: 18.19537658463833
---
![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
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# Whisper Small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the MiZonal v2.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3063
- Wer: 18.1954

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4781        | 0.66  | 500  | 0.4381          | 31.6513 |
| 0.2315        | 1.31  | 1000 | 0.3232          | 26.3651 |
| 0.2077        | 1.97  | 1500 | 0.2701          | 21.4102 |
| 0.1065        | 2.62  | 2000 | 0.2621          | 20.4574 |
| 0.051         | 3.28  | 2500 | 0.2723          | 19.9022 |
| 0.0538        | 3.93  | 3000 | 0.2631          | 19.1897 |
| 0.0227        | 4.59  | 3500 | 0.2811          | 19.3305 |
| 0.0099        | 5.24  | 4000 | 0.2904          | 19.2477 |
| 0.0092        | 5.9   | 4500 | 0.2900          | 18.6511 |
| 0.004         | 6.55  | 5000 | 0.3005          | 18.1871 |
| 0.0021        | 7.21  | 5500 | 0.3043          | 18.2948 |
| 0.0022        | 7.86  | 6000 | 0.3063          | 18.1954 |


### Framework versions

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