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whisper-kor3_de
This model is a fine-tuned version of openai/whisper-small-denoising on the whisper-kor3_de dataset. It achieves the following results on the evaluation set:
- Loss: 0.5477
- Wer: 31.5495
- Cer: 15.9235
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.366 | 0.21 | 50 | 1.0427 | 36.9851 | 17.8672 |
| 0.7035 | 0.42 | 100 | 0.7269 | 34.3514 | 17.0516 |
| 0.526 | 0.64 | 150 | 0.5843 | 35.7803 | 17.8672 |
| 0.5013 | 0.85 | 200 | 0.5556 | 33.1185 | 15.3365 |
| 0.403 | 1.06 | 250 | 0.5383 | 32.6142 | 15.2756 |
| 0.3058 | 1.27 | 300 | 0.5339 | 37.7136 | 18.9267 |
| 0.3081 | 1.48 | 350 | 0.5323 | 34.7716 | 17.3718 |
| 0.3131 | 1.69 | 400 | 0.5260 | 31.6615 | 15.8396 |
| 0.2857 | 1.91 | 450 | 0.5245 | 32.1098 | 14.8487 |
| 0.1625 | 2.12 | 500 | 0.5284 | 31.6895 | 14.8258 |
| 0.1899 | 2.33 | 550 | 0.5284 | 31.8577 | 15.8244 |
| 0.1646 | 2.54 | 600 | 0.5329 | 32.2499 | 16.4875 |
| 0.183 | 2.75 | 650 | 0.5315 | 31.5775 | 15.0393 |
| 0.179 | 2.97 | 700 | 0.5291 | 31.4374 | 14.7572 |
| 0.1048 | 3.18 | 750 | 0.5402 | 31.5775 | 14.8106 |
| 0.1057 | 3.39 | 800 | 0.5418 | 31.8296 | 15.7863 |
| 0.0965 | 3.6 | 850 | 0.5429 | 31.7456 | 15.9921 |
| 0.1098 | 3.81 | 900 | 0.5451 | 32.6422 | 16.8534 |
| 0.0902 | 4.03 | 950 | 0.5453 | 31.5495 | 15.9006 |
| 0.0795 | 4.24 | 1000 | 0.5477 | 31.5495 | 15.9235 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
