6x16/whisper-small-nan-tw-quicktrain

A Quick-trained Whisper-Small model for Nan-TW (閩南話/台語) #JL

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 (nan-tw) dataset. It achieves the following results on the evaluation set:

• Loss: 0.7699
• Cer: 138.9186

Transcription Example

(Example Source: https://sutian.moe.edu.tw/zh-hant/su/27169/)
Original sentence: 萬事起頭難。
Inference by Whisper-Small: บันซู ขี้เท่าหลัน
Inference by this model: 萬事起頭難

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: Use OptimizerNames.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: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.3511	2.9240	1000	0.7512	125.6361
0.0117	5.8480	2000	0.7479	141.2850
0.001	8.7719	3000	0.7629	136.0814
0.0006	11.6959	4000	0.7699	138.9186

Framework versions

• Transformers 4.51.3
• Pytorch 2.7.0+cu126
• Datasets 3.5.1
• Tokenizers 0.21.1