Whisper Tiny Taiwanese Simulated Android
This model is a fine-tuned version of openai/whisper-tiny on the TAT ASR Aligned dataset. It achieves the following results on the evaluation set:
- Loss: 0.6140
- Cer: 11.1506
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 681
- training_steps: 6810
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.345 | 0.9985 | 681 | 0.4722 | 17.2090 |
| 0.2022 | 1.9971 | 1362 | 0.4060 | 13.0439 |
| 0.1228 | 2.9956 | 2043 | 0.4379 | 13.2219 |
| 0.0721 | 3.9941 | 2724 | 0.4696 | 12.3827 |
| 0.0406 | 4.9927 | 3405 | 0.5141 | 12.5748 |
| 0.021 | 5.9912 | 4086 | 0.5437 | 12.2795 |
| 0.0107 | 6.9897 | 4767 | 0.5696 | 11.8216 |
| 0.0034 | 7.9883 | 5448 | 0.5935 | 11.4186 |
| 0.0011 | 8.9868 | 6129 | 0.6080 | 11.2588 |
| 0.0006 | 9.9853 | 6810 | 0.6140 | 11.1506 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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openai/whisper-tiny