This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2352
Wer: 8.1166
Cer: 5.0032

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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	Cer
0.0897	0.1	1000	0.1884	11.0068	6.6992
0.0396	0.2	2000	0.1749	9.7399	5.9350
0.036	1.1	3000	0.1698	9.1419	5.6781
0.012	1.2	4000	0.1849	9.3041	5.7661
0.0151	2.09	5000	0.1879	9.1959	5.6761
0.0047	2.19	6000	0.2097	8.6706	5.4422
0.0046	3.09	7000	0.2040	8.8277	5.4717
0.0015	3.19	8000	0.2260	8.4949	5.3101
0.0013	4.09	9000	0.2339	8.3716	5.1471
0.0005	4.19	10000	0.2352	8.1166	5.0032

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2

vumichien/whisper-large-v2-jp

openai/whisper-large-v2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vumichien/
whisper-large-v2-jp