This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 ja dataset. It achieves the following results on the evaluation set:

Loss: 0.4232
Wer: 13.4679
Cer: 8.6022

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: 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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0167	7.0	1000	0.3066	13.6740	8.5733
0.0021	14.01	2000	0.3579	13.8733	8.7816
0.0006	21.01	3000	0.4025	13.5794	8.6173
0.0004	28.01	4000	0.4232	13.4679	8.6022
0.0004	35.01	5000	0.4319	13.4747	8.6213

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.7.1.dev0
Tokenizers 0.13.2

vumichien/whisper-small-ja

Whisper Small Japanese

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vumichien/
whisper-small-ja