Whisper Small Taiwanese
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: 0.9011
- Cer: 50.3995
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.6
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 1.1421 | 0.4 | 1000 | 61.1639 | 1.1692 |
| 1.0556 | 0.8 | 2000 | 51.7749 | 1.0215 |
| 0.7837 | 1.2 | 3000 | 54.1978 | 0.9572 |
| 0.7332 | 1.6 | 4000 | 50.3966 | 0.9230 |
| 0.6957 | 2.0 | 5000 | 50.5772 | 0.9064 |
| 0.6211 | 2.4 | 6000 | 0.9177 | 49.8590 |
| 0.5584 | 2.8 | 7000 | 0.8962 | 47.5366 |
| 0.3952 | 3.2 | 8000 | 0.9025 | 48.2925 |
| 0.4248 | 3.6 | 9000 | 0.9011 | 50.3995 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-small