---
language:
- zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- formospeech/tat_asr_aligned
model-index:
- name: Whisper Tiny Taiwanese Android
  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 Tiny Taiwanese Android

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the TAT ASR Aligned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6536
- Cer: 10.3016

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1362
- training_steps: 13620
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Cer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.371         | 0.9985  | 681   | 0.4334          | 14.4492 |
| 0.2637        | 1.9971  | 1362  | 0.3950          | 13.0672 |
| 0.1725        | 2.9956  | 2043  | 0.3962          | 12.1858 |
| 0.1102        | 3.9941  | 2724  | 0.4102          | 11.8710 |
| 0.0715        | 4.9927  | 3405  | 0.4442          | 11.9113 |
| 0.0467        | 5.9912  | 4086  | 0.4830          | 12.2436 |
| 0.0322        | 6.9897  | 4767  | 0.5100          | 11.6466 |
| 0.0234        | 7.9883  | 5448  | 0.5315          | 11.5878 |
| 0.0182        | 8.9868  | 6129  | 0.5542          | 11.8786 |
| 0.012         | 9.9853  | 6810  | 0.5834          | 11.5762 |
| 0.0083        | 10.9839 | 7491  | 0.5833          | 11.4945 |
| 0.0061        | 11.9824 | 8172  | 0.6000          | 11.1774 |
| 0.0045        | 12.9809 | 8853  | 0.6136          | 11.0700 |
| 0.0027        | 13.9795 | 9534  | 0.6144          | 10.8808 |
| 0.0008        | 14.9780 | 10215 | 0.6320          | 10.6295 |
| 0.0006        | 15.9765 | 10896 | 0.6380          | 10.6150 |
| 0.0003        | 16.9751 | 11577 | 0.6385          | 10.4755 |
| 0.0003        | 17.9736 | 12258 | 0.6498          | 10.4047 |
| 0.0001        | 18.9721 | 12939 | 0.6537          | 10.3546 |
| 0.0001        | 19.9707 | 13620 | 0.6536          | 10.3016 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1