Whisper Small Taiwanese
This model is a fine-tuned version of openai/whisper-small on the Common Voice 14.0, 15.0 and 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3536
- Wer: 70.2194
Model description
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Intended uses & limitations
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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
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.4161 | 0.32 | 1000 | 0.4634 | 83.0040 |
0.2973 | 0.64 | 2000 | 0.3831 | 73.8176 |
0.229 | 0.97 | 3000 | 0.3536 | 70.2194 |
Framework versions
- Transformers 4.39.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-small