whisper-medium-chinese-tw-minnan
This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0459
- Wer: 75.3550
- Cer: 42.1433
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0997 | 3.6381 | 1000 | 1.0399 | 82.0487 | 48.6755 |
| 0.0131 | 7.2735 | 2000 | 1.0279 | 75.9635 | 43.4377 |
| 0.0009 | 10.9116 | 3000 | 1.0553 | 75.4564 | 43.2872 |
| 0.0001 | 14.5469 | 4000 | 1.0423 | 75.5578 | 42.6851 |
| 0.0 | 18.1823 | 5000 | 1.0459 | 75.3550 | 42.1433 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1