---
language:
- yue
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Jyutping without Tones (Trained on almost all open source Cantonese
    datasets)
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Jyutping without Tones (Trained on almost all open source Cantonese datasets)

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 14.0 Yue & zh-HK + MDCC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0560
- Wer: 5.5162

## 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: 16
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0655        | 0.07  | 1000 | 0.0948          | 8.6022 |
| 0.0577        | 0.13  | 2000 | 0.0747          | 6.9833 |
| 0.0496        | 0.2   | 3000 | 0.0627          | 6.8633 |
| 0.0558        | 0.27  | 4000 | 0.0560          | 5.5162 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3