Wisper-Small-zh-TW
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2284
- Cer: 10.0577
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.1053 | 1.3245 | 1000 | 0.2142 | 10.8687 |
| 0.0322 | 2.6490 | 2000 | 0.2128 | 10.3917 |
| 0.0086 | 3.9735 | 3000 | 0.2213 | 10.1155 |
| 0.0023 | 5.2980 | 4000 | 0.2284 | 10.0577 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1
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