This model is a fine-tuned version of imTak/whisper_large_v3_ko_ft_ft on the Economy dataset. It achieves the following results on the evaluation set:

Loss: 0.7148
Wer: 44.9921

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: linear
lr_scheduler_warmup_steps: 500
training_steps: 8000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8263	0.4630	1000	0.8210	49.0241
0.7497	0.9259	2000	0.7351	47.6006
0.4979	1.3889	3000	0.6992	45.6375
0.5197	1.8519	4000	0.6659	44.3410
0.4264	2.3148	5000	0.7168	46.6459
0.3911	2.7778	6000	0.6988	45.0726
0.2565	3.2407	7000	0.7203	44.8000
0.2462	3.7037	8000	0.7148	44.9921

Framework versions

Transformers 4.45.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

imTak/whisper_large_v3_turbo_korean_Economy

Whisper large v3 turbo Korean-Economy

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

imTak/
whisper_large_v3_turbo_korean_Economy