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

Loss: 0.4385
Wer: 17.0732

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 200
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0002	111.0	1000	0.2155	9.7561
0.0001	222.0	2000	0.2448	12.1951
0.0	333.0	3000	0.2674	13.4146
0.0	444.0	4000	0.2943	15.8537
0.0	555.0	5000	0.3182	17.0732
0.0	666.0	6000	0.3501	18.9024
0.0	777.0	7000	0.3732	16.4634
0.0	888.0	8000	0.4025	17.0732
0.0	999.0	9000	0.4178	20.1220
0.0	1111.0	10000	0.4385	17.0732

Framework versions

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

noflm/whisper-base-ja-elite

Whisper Base Japanese Elite

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

noflm/
whisper-base-ja-elite