This model is a fine-tuned version of openai/whisper-small on the gacky1601/Taiwanese_ASR dataset. It achieves the following results on the evaluation set:

Loss: 0.2297
Wer: 6.0497

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: 6
eval_batch_size: 6
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: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.083	2.2676	1000	0.1953	8.1731
0.0444	4.5351	2000	0.1973	6.9444
0.0294	6.8027	3000	0.1984	6.5171
0.0334	9.0703	4000	0.2099	6.3034
0.0011	11.3379	5000	0.2229	6.3835
0.0001	13.6054	6000	0.2200	6.2099
0.0001	15.8730	7000	0.2297	6.0497
0.0001	18.1406	8000	0.2317	6.0764
0.0001	20.4082	9000	0.2375	6.3969
0.0	22.6757	10000	0.2379	6.4904

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.20.3

gacky1601/whisper-small-taiwanese-asr-v2

whisper-small-taiwanese-asr-v2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gacky1601/
whisper-small-taiwanese-asr-v2