---
language:
- nan
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
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 15.0 and 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3916
- Wer: 68.5703

## 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
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4172        | 0.32  | 1000 | 0.4641          | 82.9494 |
| 0.2962        | 0.64  | 2000 | 0.3834          | 73.8040 |
| 0.229         | 0.97  | 3000 | 0.3537          | 70.0423 |
| 0.1994        | 1.29  | 4000 | 0.3685          | 71.1599 |
| 0.1693        | 1.61  | 5000 | 0.3551          | 67.8206 |
| 0.1398        | 1.93  | 6000 | 0.3526          | 67.6707 |
| 0.1032        | 2.25  | 7000 | 0.3836          | 69.4834 |
| 0.0745        | 2.58  | 8000 | 0.3839          | 68.5566 |
| 0.0558        | 2.9   | 9000 | 0.3916          | 68.5703 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2