Whisper Small Taiwanese (Min Nan)
This model is a fine-tuned version of openai/whisper-small on the Taiwanese Songs (Min Nan) dataset. It achieves the following results on the evaluation set:
- Loss: 2.6304
- Wer: 25.6671
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: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 200
- training_steps: 10000
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5742 | 2.3284 | 100 | 3.5014 | 66.2008 |
| 1.9713 | 4.6569 | 200 | 2.6350 | 45.9975 |
| 1.5884 | 6.9853 | 300 | 2.4657 | 36.0864 |
| 1.5118 | 9.3050 | 400 | 2.5327 | 34.5616 |
| 1.4857 | 11.6334 | 500 | 2.5065 | 33.7992 |
| 1.4703 | 13.9619 | 600 | 2.4858 | 30.7497 |
| 1.459 | 16.2815 | 700 | 2.4334 | 28.3355 |
| 1.4511 | 18.6100 | 800 | 2.4682 | 28.9708 |
| 1.4472 | 20.9384 | 900 | 2.4897 | 29.3520 |
| 1.4435 | 23.2581 | 1000 | 2.5269 | 42.8208 |
| 1.4377 | 25.5865 | 1100 | 2.5061 | 26.9377 |
| 1.4364 | 27.9150 | 1200 | 2.5459 | 26.9377 |
| 1.4328 | 30.2346 | 1300 | 2.5174 | 28.0813 |
| 1.4334 | 32.5630 | 1400 | 2.5495 | 26.1753 |
| 1.429 | 34.8915 | 1500 | 2.5535 | 26.1753 |
| 1.427 | 37.2111 | 1600 | 2.5565 | 26.6836 |
| 1.4254 | 39.5396 | 1700 | 2.5540 | 25.0318 |
| 1.4241 | 41.8680 | 1800 | 2.5546 | 26.9377 |
| 1.423 | 44.1877 | 1900 | 2.5845 | 26.3024 |
| 1.4224 | 46.5161 | 2000 | 2.5926 | 26.4295 |
| 1.4215 | 48.8446 | 2100 | 2.6072 | 26.1753 |
| 1.4212 | 51.1642 | 2200 | 2.6304 | 25.6671 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.7.1+cu118
- Datasets 4.1.1
- Tokenizers 0.22.1