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