Whisper Small Taiwanese
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 and the Common Voice 15.0 datasets. It achieves the following results on the evaluation set:
- Loss: 0.3736
- Cer: 29.6973
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: 100
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 0.7938 | 0.16 | 500 | 55.8341 | 0.7768 |
| 0.5845 | 0.32 | 1000 | 41.1522 | 0.5947 |
| 0.459 | 0.48 | 1500 | 37.6183 | 0.5132 |
| 0.3512 | 0.64 | 2000 | 35.4047 | 0.4709 |
| 0.3758 | 0.8 | 2500 | 33.5778 | 0.4363 |
| 0.3191 | 0.96 | 3000 | 32.6110 | 0.4216 |
| 0.2295 | 1.13 | 3500 | 0.4261 | 32.4977 |
| 0.1806 | 1.29 | 4000 | 0.4085 | 31.9909 |
| 0.16 | 1.45 | 4500 | 0.3913 | 31.1708 |
| 0.1603 | 1.61 | 5000 | 0.3836 | 30.3841 |
| 0.1343 | 1.77 | 5500 | 0.3784 | 30.1574 |
| 0.1265 | 1.93 | 6000 | 0.3736 | 29.6973 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2