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

Loss: 0.7525
Wer: 42.5930
Cer: 23.2970

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: 2
eval_batch_size: 2
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
0.4781	1.04	1000	0.7256	52.4690	28.7583
0.1881	2.08	2000	0.7346	50.2067	26.6389
0.0429	3.13	3000	0.7094	45.3557	24.7811
0.0112	5.01	4000	0.7416	44.4203	24.6850
0.0011	6.05	5000	0.7525	42.5930	23.2970

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2

thomas0104/whisper_large_v2_nan_tw

Whisper large-v2 nan-tw

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

thomas0104/
whisper_large_v2_nan_tw