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whisper-base-zh-20230724 - au2a
This model is a fine-tuned version of openai/whisper-base on the some hakka audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.4868
- Cer: 21.2071
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: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.348 | 1.55 | 1000 | 0.6190 | 30.1519 |
| 0.1375 | 3.1 | 2000 | 0.4988 | 23.8969 |
| 0.0741 | 4.65 | 3000 | 0.4735 | 22.7089 |
| 0.0348 | 6.2 | 4000 | 0.4643 | 21.9984 |
| 0.0211 | 7.75 | 5000 | 0.4688 | 22.1851 |
| 0.0102 | 9.3 | 6000 | 0.4738 | 21.3982 |
| 0.0076 | 10.85 | 7000 | 0.4762 | 21.3477 |
| 0.0049 | 12.4 | 8000 | 0.4820 | 21.3352 |
| 0.0044 | 13.95 | 9000 | 0.4859 | 21.1040 |
| 0.0036 | 15.5 | 10000 | 0.4868 | 21.2071 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
