---
language:
- yue
license: apache-2.0
base_model: poppysmickarlili/whisper-small-cantonese_07-05-2024-2200
tags:
- generated_from_trainer
datasets:
- poppysmickarlili/common_voice_yue
metrics:
- wer
model-index:
- name: Whisper Small Cantanese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: poppysmickarlili/common_voice_yue
      type: poppysmickarlili/common_voice_yue
      args: 'config: yue, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.017123287671232876
---

<!-- 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 Cantanese

This model is a fine-tuned version of [poppysmickarlili/whisper-small-cantonese_07-05-2024-2200](https://huggingface.co/poppysmickarlili/whisper-small-cantonese_07-05-2024-2200) on the poppysmickarlili/common_voice_yue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0171

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0039        | 2.7816  | 1000 | 0.0040          | 1.3699 |
| 0.0006        | 5.5633  | 2000 | 0.0001          | 0.0514 |
| 0.0001        | 8.3449  | 3000 | 0.0001          | 0.0171 |
| 0.0           | 11.1377 | 4000 | 0.0000          | 0.0171 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1