This model is a fine-tuned version of openai/whisper-small on the Elite35P-Server/EliteVoiceProject youtube dataset. It achieves the following results on the evaluation set:

Loss: 1.1596
Wer: 31.5364

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: constant_with_warmup
lr_scheduler_warmup_steps: 100
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0003	52.0	1000	0.8053	28.8410
0.0	105.0	2000	0.8636	28.5714
0.0	157.0	3000	0.9056	28.0323
0.0	210.0	4000	0.9414	28.8410
0.0	263.0	5000	0.9842	31.2668
0.0	315.0	6000	1.0223	31.2668
0.0	368.0	7000	1.0677	31.2668
0.0	421.0	8000	1.1079	31.2668
0.0	473.0	9000	1.1468	31.5364
0.0	526.0	10000	1.1596	31.5364

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.1.dev0
Tokenizers 0.13.2

noflm/whisper-small-ja-elite

Whisper Small Japanese Elite

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

noflm/
whisper-small-ja-elite