---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Maori
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs mi_nz
      type: google/fleurs
      config: mi_nz
      split: test
      args: mi_nz
    metrics:
    - name: Wer
      type: wer
      value: 30.481593707691317
---

<!-- 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 Maori

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs mi_nz dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7756
- Wer: 30.4816

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2693        | 7.02  | 100  | 0.6741          | 35.4845 |
| 0.0084        | 15.01 | 200  | 0.7756          | 30.4816 |
| 0.0029        | 23.0  | 300  | 0.8154          | 31.4744 |
| 0.002         | 30.02 | 400  | 0.8320          | 31.3777 |
| 0.0017        | 38.01 | 500  | 0.8372          | 31.5163 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2