Whisper Large Korean/English
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8019
- Wer: 198.2263
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 773
- training_steps: 7728
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5546 | 1.0 | 773 | 0.5308 | 240.1463 |
| 0.3284 | 2.0 | 1546 | 0.5160 | 133.6395 |
| 0.176 | 3.0 | 2319 | 0.5582 | 264.5033 |
| 0.0977 | 4.0 | 3092 | 0.6110 | 155.6417 |
| 0.065 | 5.0 | 3865 | 0.6577 | 194.4118 |
| 0.0298 | 6.0 | 4638 | 0.7021 | 235.0691 |
| 0.0109 | 7.0 | 5411 | 0.7408 | 158.8282 |
| 0.0069 | 8.0 | 6184 | 0.7550 | 201.9574 |
| 0.0057 | 9.0 | 6957 | 0.8019 | 198.2263 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1
- Datasets 2.17.0
- Tokenizers 0.15.2
- Downloads last month
- 3