Whisper Small zh-TW
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2504
Cer: 10.4045
But when loaded CER = 10.3295
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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0898 | 1.38 | 1000 | 0.1981 | 11.5149 |
| 0.0283 | 2.75 | 2000 | 0.1991 | 10.3994 |
| 0.0037 | 4.13 | 3000 | 0.2141 | 10.5107 |
| 0.0038 | 5.5 | 4000 | 0.2237 | 10.4252 |
| 0.0033 | 6.88 | 5000 | 0.2263 | 10.3062 |
| 0.0004 | 8.25 | 6000 | 0.2339 | 10.8238 |
| 0.0003 | 9.63 | 7000 | 0.2400 | 10.4252 |
| 0.0002 | 11.0 | 8000 | 0.2451 | 10.5262 |
| 0.0002 | 12.38 | 9000 | 0.2487 | 10.3605 |
| 0.0002 | 13.76 | 10000 | 0.2504 | 10.4045 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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