---
library_name: transformers
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 (topline)
  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 (topline)

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: 1.0400
- Cer: 20.3105

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.6758        | 0.9985  | 681   | 0.6816          | 35.6624 |
| 0.5019        | 1.9971  | 1362  | 0.6077          | 24.6575 |
| 0.3484        | 2.9956  | 2043  | 0.5875          | 23.5932 |
| 0.2444        | 3.9941  | 2724  | 0.6029          | 22.1000 |
| 0.16          | 4.9927  | 3405  | 0.6502          | 22.3178 |
| 0.1084        | 5.9912  | 4086  | 0.7111          | 22.3447 |
| 0.0728        | 6.9897  | 4767  | 0.7801          | 22.1145 |
| 0.0493        | 7.9883  | 5448  | 0.8294          | 22.0905 |
| 0.0333        | 8.9868  | 6129  | 0.8626          | 22.4998 |
| 0.0248        | 9.9853  | 6810  | 0.8916          | 21.6134 |
| 0.018         | 10.9839 | 7491  | 0.9241          | 21.7539 |
| 0.0122        | 11.9824 | 8172  | 0.9620          | 21.7042 |
| 0.0086        | 12.9809 | 8853  | 0.9697          | 21.6206 |
| 0.0064        | 13.9795 | 9534  | 0.9937          | 21.1544 |
| 0.0037        | 14.9780 | 10215 | 1.0012          | 21.0531 |
| 0.0021        | 15.9765 | 10896 | 1.0125          | 20.6351 |
| 0.0015        | 16.9751 | 11577 | 1.0279          | 20.4550 |
| 0.0015        | 17.9736 | 12258 | 1.0328          | 20.2847 |
| 0.0018        | 18.9721 | 12939 | 1.0392          | 20.3533 |
| 0.0011        | 19.9707 | 13620 | 1.0400          | 20.3105 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.0.0.post304
- Datasets 3.3.2
- Tokenizers 0.21.0