This model is a fine-tuned version of openai/whisper-base on the TARARARAK/KsponSpeech_01_ALHUB_preprocess dataset. It achieves the following results on the evaluation set:

Loss: 0.4357
Cer: 14.3015

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: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.5007	0.2690	1000	0.5043	17.1656
0.4516	0.5381	2000	0.4650	15.5761
0.4293	0.8071	3000	0.4440	14.9569
0.3653	1.0761	4000	0.4357	14.3015

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1

TARARARAK/Whisper_Korean_fine-tune

Whisper_Korean_fine-tune

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TARARARAK/
Whisper_Korean_fine-tune