This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

Loss: 1.0601
Wer: 280.9249

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
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2485	3.05	1000	0.9971	538.5505
0.0154	6.1	2000	1.0482	1460.5158
0.0024	9.15	3000	1.0330	261.3161
0.0014	12.2	4000	1.0554	300.3112
0.0003	15.24	5000	1.0601	280.9249

Framework versions

Transformers 4.37.1
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

tyty979812/nan-tw-whisper-large-v3

Whisper large-v3 nan-tw

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tyty979812/
nan-tw-whisper-large-v3