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whisper-small-zh-20230714-1 - au2a
This model is a fine-tuned version of openai/whisper-small on the some hakka audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.3765
- Cer: 85.1930
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: 64
- 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 |
|---|---|---|---|---|
| 0.1072 | 1.29 | 1000 | 0.3484 | 60.5235 |
| 0.0176 | 2.59 | 2000 | 0.3341 | 58.3327 |
| 0.0031 | 3.88 | 3000 | 0.3407 | 76.3806 |
| 0.0015 | 5.17 | 4000 | 0.3496 | 72.6222 |
| 0.001 | 6.47 | 5000 | 0.3591 | 64.4028 |
| 0.0012 | 7.76 | 6000 | 0.3598 | 51.4316 |
| 0.0005 | 9.06 | 7000 | 0.3663 | 69.3171 |
| 0.0004 | 10.35 | 8000 | 0.3696 | 81.2420 |
| 0.0003 | 11.64 | 9000 | 0.3746 | 84.8833 |
| 0.0003 | 12.94 | 10000 | 0.3765 | 85.1930 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
