This model is a fine-tuned version of openai/whisper-small on the Common Voice 8.0 Japanese dataset. It achieves the following results on the evaluation set:

Loss: 0.3763
Wer: 72.2467

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: 8000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0349	3.7453	1000	0.2838	71.8062
0.0031	7.4906	2000	0.3100	69.6035
0.0007	11.2360	3000	0.3358	70.9251
0.0003	14.9813	4000	0.3474	73.5683
0.0002	18.7266	5000	0.3555	73.1278
0.0002	22.4719	6000	0.3663	73.1278
0.0001	26.2172	7000	0.3732	72.2467
0.0001	29.9625	8000	0.3763	72.2467

Framework versions

Transformers 5.1.0
Pytorch 2.5.1+cu121
Datasets 2.21.0
Tokenizers 0.22.2

kdl02/whisper-small-ja

Whisper Small Japanese - Your Name

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kdl02/
whisper-small-ja