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PThi35/
imTak_whisper_large_v3_turbo_Korean2

Name: imTak_whisper_large_v3_turbo_Korean2
Availability: InStock

automatic-speech-recognition

generated_from_trainer

imTak/whisper_large_v3_turbo_Korean2

finetune

mit

endpoints_compatible

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imTak_whisper_large_v3_turbo_Korean2

This model is a fine-tuned version of imTak/whisper_large_v3_turbo_Korean2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.8328
Cer: 93.7918
Wer: 135.0419

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.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: 1000
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer
4.9896	1.0	1056	4.2730	267.6030	483.5622
4.2422	2.0	2112	4.1516	253.8467	410.7671
3.7231	3.0	3168	2.2834	165.7367	230.1853
2.2021	4.0	4224	1.8891	98.9525	143.1385
1.7945	5.0	5280	1.8328	93.7918	135.0419

Framework versions

Transformers 4.55.4
Pytorch 2.8.0+cu126
Datasets 4.1.1
Tokenizers 0.21.4

PThi35/imTak_whisper_large_v3_turbo_Korean2

imTak_whisper_large_v3_turbo_Korean2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

PThi35/
imTak_whisper_large_v3_turbo_Korean2