---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
model-index:
- name: Whisper Small zh-TW
  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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2504
- Cer: 10.4045

- But when loaded CER = 10.3295

## 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0898        | 1.38  | 1000  | 0.1981          | 11.5149 |
| 0.0283        | 2.75  | 2000  | 0.1991          | 10.3994 |
| 0.0037        | 4.13  | 3000  | 0.2141          | 10.5107 |
| 0.0038        | 5.5   | 4000  | 0.2237          | 10.4252 |
| 0.0033        | 6.88  | 5000  | 0.2263          | 10.3062 |
| 0.0004        | 8.25  | 6000  | 0.2339          | 10.8238 |
| 0.0003        | 9.63  | 7000  | 0.2400          | 10.4252 |
| 0.0002        | 11.0  | 8000  | 0.2451          | 10.5262 |
| 0.0002        | 12.38 | 9000  | 0.2487          | 10.3605 |
| 0.0002        | 13.76 | 10000 | 0.2504          | 10.4045 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2