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URL: https://huggingface.co/seastar105/whisper-medium-ko-zeroth

⇱ seastar105/whisper-medium-ko-zeroth · Hugging Face

적지 않은 분들이 다운로드하셔서 사용하는 걸로 보입니다. https://huggingface.co/seastar105/whisper-medium-komixv2 에 더 좋은 정확도를 기대 가능한 파인튜닝 모델이 있으므로 이쪽을 추천합니다.

Whisper Medium Korean

This model is a fine-tuned version of openai/whisper-medium on the Zeroth Korean dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0727
  • Wer: 3.6440
  • Cer: 1.4840

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: 5e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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
0.0873 0.72 1000 0.1086 7.7549 2.5597
0.0258 1.44 2000 0.0805 4.5475 1.7588
0.0091 2.16 3000 0.0719 3.7946 1.5664
0.0086 2.88 4000 0.0704 3.5537 1.5232
0.0019 3.59 5000 0.0727 3.6440 1.4840

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0a0+d0d6b1f
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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