Whisper Large V2 Cantonese
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 yue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2807
- Cer: 6.7274
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: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Cer |
|---|---|---|---|---|
| 0.0032 | 13.01 | 1000 | 0.2318 | 6.8569 |
| 0.002 | 26.01 | 2000 | 0.2404 | 7.1524 |
| 0.0001 | 39.02 | 3000 | 0.2807 | 6.7274 |
| 0.0001 | 53.01 | 4000 | 0.2912 | 6.7517 |
| 0.0 | 66.01 | 5000 | 0.2957 | 6.7638 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train simonl0909/whisper-large-v2-cantonese
Space using simonl0909/whisper-large-v2-cantonese 1
Evaluation results
- Cer on mozilla-foundation/common_voice_11_0test set self-reported6.727
- Test CER on Common Voice zh-HKself-reported6.727