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Finetuning_Whisper_Ko – AI Model by YongJaeLee | AlphaNeural AI
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Finetuning_Whisper_Ko
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
ko
DragonJae/Whisper_FineTuning_Ko_preprocessing
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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Finetuning_Whisper_Ko
This model is a fine-tuned version of
openai/whisper-base
on the 저음질 전화음성 데이터 dataset. It achieves the following results on the evaluation set:
Loss: 0.4382
Cer: 16.7767
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.6311
0.5010
1000
0.6099
27.3330
0.495
1.0020
2000
0.5025
19.3769
0.4176
1.5030
3000
0.4573
17.4759
0.3789
2.0040
4000
0.4382
16.7767
Framework versions
Transformers 4.52.0.dev0
Pytorch 2.5.1+cu121
Datasets 3.6.0
Tokenizers 0.21.1
