whisper-small-chinese-tw-minnan-hanzi
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2235
- Wer: 86.7140
- Cer: 62.5226
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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 |
|---|---|---|---|---|---|
| 0.0802 | 3.6364 | 1000 | 1.1582 | 91.0751 | 80.0120 |
| 0.0014 | 7.2727 | 2000 | 1.1876 | 85.8012 | 61.7399 |
| 0.0002 | 10.9091 | 3000 | 1.1944 | 85.4970 | 61.7098 |
| 0.0002 | 14.5455 | 4000 | 1.2139 | 85.8012 | 61.8603 |
| 0.0001 | 18.1818 | 5000 | 1.2235 | 86.7140 | 62.5226 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3