---
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
- mozilla-foundation/common_voice_15_0
model-index:
- name: Whisper Small Taiwanese
  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 Taiwanese

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 and the Common Voice 15.0 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.3736
- Cer: 29.6973

## 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: 100
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Cer     | Validation Loss |
|:-------------:|:-----:|:----:|:-------:|:---------------:|
| 0.7938        | 0.16  | 500  | 55.8341 | 0.7768          |
| 0.5845        | 0.32  | 1000 | 41.1522 | 0.5947          |
| 0.459         | 0.48  | 1500 | 37.6183 | 0.5132          |
| 0.3512        | 0.64  | 2000 | 35.4047 | 0.4709          |
| 0.3758        | 0.8   | 2500 | 33.5778 | 0.4363          |
| 0.3191        | 0.96  | 3000 | 32.6110 | 0.4216          |
| 0.2295        | 1.13  | 3500 | 0.4261  | 32.4977         |
| 0.1806        | 1.29  | 4000 | 0.4085  | 31.9909         |
| 0.16          | 1.45  | 4500 | 0.3913  | 31.1708         |
| 0.1603        | 1.61  | 5000 | 0.3836  | 30.3841         |
| 0.1343        | 1.77  | 5500 | 0.3784  | 30.1574         |
| 0.1265        | 1.93  | 6000 | 0.3736  | 29.6973         |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2