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whisper-medium-zh-20230712 - au2a
This model is a fine-tuned version of openai/whisper-medium on the some hakka audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.2659
- Cer: 87.6898
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: 5e-06
- train_batch_size: 8
- 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: 15000
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.2417 | 0.16 | 1000 | 0.3919 | 92.1659 |
| 0.1219 | 0.32 | 2000 | 0.2963 | 81.3855 |
| 0.0762 | 0.49 | 3000 | 0.2785 | 68.9544 |
| 0.0524 | 0.65 | 4000 | 0.2660 | 89.4916 |
| 0.0347 | 0.81 | 5000 | 0.2517 | 96.8800 |
| 0.0255 | 0.97 | 6000 | 0.2567 | 89.0232 |
| 0.0104 | 1.13 | 7000 | 0.2547 | 91.9959 |
| 0.0069 | 1.29 | 8000 | 0.2609 | 85.5481 |
| 0.0072 | 1.46 | 9000 | 0.2605 | 72.8148 |
| 0.0081 | 1.62 | 10000 | 0.2593 | 81.8161 |
| 0.0024 | 1.78 | 11000 | 0.2608 | 79.6064 |
| 0.0021 | 1.94 | 12000 | 0.2622 | 78.2655 |
| 0.0004 | 2.1 | 13000 | 0.2656 | 86.0580 |
| 0.0005 | 2.27 | 14000 | 0.2665 | 90.1677 |
| 0.0005 | 2.43 | 15000 | 0.2659 | 87.6898 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.11.0+cu113
- Datasets 2.13.1
- Tokenizers 0.13.3
