---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
model-index:
- name: Whisper Small zh-TW - Chinese
  results: []
---

<!-- 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 zh-TW - Chinese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2102
- Cer: 125.9209

## 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: 8
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0977        | 1.33  | 1000 | 0.1988          | 92.1973  |
| 0.04          | 2.65  | 2000 | 0.1952          | 127.6179 |
| 0.0102        | 3.98  | 3000 | 0.2032          | 152.5090 |
| 0.0017        | 5.31  | 4000 | 0.2102          | 125.9209 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0.post301
- Datasets 2.16.1
- Tokenizers 0.15.0