---
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: lab9_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: 62.13592233009708
---

<!-- 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. -->

# lab9_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: 0.6336
- Wer Ortho: 64.0
- Wer: 62.1359

## 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     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.0088        | 0.6882 | 500  | 0.5502          | 60.0      | 61.1650 |
| 0.0051        | 1.3765 | 1000 | 0.5735          | 65.0      | 64.0777 |
| 0.0068        | 2.0647 | 1500 | 0.5820          | 63.0      | 63.1068 |
| 0.0021        | 2.7529 | 2000 | 0.5955          | 62.0      | 61.1650 |
| 0.0039        | 3.4412 | 2500 | 0.5858          | 62.0      | 61.1650 |
| 0.0018        | 4.1294 | 3000 | 0.5981          | 63.0      | 61.1650 |
| 0.0019        | 4.8176 | 3500 | 0.6322          | 63.0      | 61.1650 |
| 0.0102        | 5.5058 | 4000 | 0.6336          | 64.0      | 62.1359 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1