---
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 Simulated 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 Simulated 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: 0.7438
- Cer: 11.6466

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3611        | 0.9985  | 681   | 0.4700          | 20.9285 |
| 0.2547        | 1.9971  | 1362  | 0.4463          | 15.1381 |
| 0.1658        | 2.9956  | 2043  | 0.4418          | 13.8355 |
| 0.1045        | 3.9941  | 2724  | 0.4723          | 13.4539 |
| 0.0687        | 4.9927  | 3405  | 0.4987          | 13.4172 |
| 0.0456        | 5.9912  | 4086  | 0.5397          | 13.2578 |
| 0.0326        | 6.9897  | 4767  | 0.5761          | 12.9786 |
| 0.0219        | 7.9883  | 5448  | 0.6007          | 13.0098 |
| 0.0167        | 8.9868  | 6129  | 0.6061          | 12.7120 |
| 0.0122        | 9.9853  | 6810  | 0.6446          | 12.8573 |
| 0.0087        | 10.9839 | 7491  | 0.6544          | 12.7846 |
| 0.0053        | 11.9824 | 8172  | 0.6783          | 12.3071 |
| 0.0041        | 12.9809 | 8853  | 0.6960          | 12.3634 |
| 0.002         | 13.9795 | 9534  | 0.7046          | 12.2334 |
| 0.0012        | 14.9780 | 10215 | 0.7138          | 12.0635 |
| 0.0004        | 15.9765 | 10896 | 0.7239          | 12.0304 |
| 0.0002        | 16.9751 | 11577 | 0.7270          | 11.7646 |
| 0.0001        | 17.9736 | 12258 | 0.7367          | 11.6746 |
| 0.0001        | 18.9721 | 12939 | 0.7418          | 11.6619 |
| 0.0001        | 19.9707 | 13620 | 0.7438          | 11.6466 |


### Framework versions

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