---
license: apache-2.0
base_model: Wellyowo/whisper-tiny-zh-tw
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-tiny-zh-tw
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: zh-TW
      split: test
      args: zh-TW
    metrics:
    - name: Wer
      type: wer
      value: 59.22330097087378
---

<!-- 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-tiny-zh-tw

This model is a fine-tuned version of [Wellyowo/whisper-tiny-zh-tw](https://huggingface.co/Wellyowo/whisper-tiny-zh-tw) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5683
- Wer Ortho: 60.0
- Wer: 59.2233

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.1844        | 0.69  | 500  | 0.5523          | 64.0      | 65.0485 |
| 0.1105        | 1.38  | 1000 | 0.5425          | 65.0      | 64.0777 |
| 0.0475        | 2.06  | 1500 | 0.5324          | 63.0      | 64.0777 |
| 0.0687        | 2.75  | 2000 | 0.5128          | 62.0      | 61.1650 |
| 0.0371        | 3.44  | 2500 | 0.5496          | 64.0      | 64.0777 |
| 0.0181        | 4.13  | 3000 | 0.5339          | 62.0      | 63.1068 |
| 0.0202        | 4.82  | 3500 | 0.5474          | 65.0      | 64.0777 |
| 0.011         | 5.51  | 4000 | 0.5683          | 60.0      | 59.2233 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1