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Whisper Small Chinese
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 zh-CN dataset. It achieves the following results on the evaluation set:
- Loss: 0.3226
- Cer: 10.9782
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 |
|---|---|---|---|---|
| 0.3998 | 0.1 | 1000 | 0.2898 | 19.1261 |
| 0.2414 | 1.07 | 2000 | 0.2826 | 12.7761 |
| 0.1197 | 2.04 | 3000 | 0.2952 | 12.4320 |
| 0.2034 | 3.0 | 4000 | 0.2962 | 13.1970 |
| 0.0344 | 3.1 | 5000 | 0.3039 | 11.5122 |
| 0.0226 | 4.07 | 6000 | 0.3083 | 11.3549 |
| 0.0097 | 5.04 | 7000 | 0.3187 | 11.4440 |
| 0.0121 | 6.01 | 8000 | 0.3173 | 11.2258 |
| 0.0015 | 6.11 | 9000 | 0.3219 | 11.1410 |
| 0.0019 | 7.07 | 10000 | 0.3226 | 10.9782 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2
