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Whisper Small LoRA tuned zh-TW
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2094
- CER: 13.1583%
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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2284 | 1.0 | 1453 | 0.2305 |
| 0.2221 | 2.0 | 2906 | 0.2183 |
| 0.1939 | 3.0 | 4359 | 0.2149 |
| 0.2085 | 4.0 | 5812 | 0.2125 |
| 0.2202 | 5.0 | 7265 | 0.2112 |
| 0.2097 | 6.0 | 8718 | 0.2103 |
| 0.2072 | 7.0 | 10171 | 0.2095 |
| 0.1906 | 8.0 | 11624 | 0.2094 |
| 0.1818 | 9.0 | 13077 | 0.2091 |
| 0.2054 | 10.0 | 14530 | 0.2093 |
| 0.1597 | 11.0 | 15983 | 0.2094 |
| 0.1797 | 12.0 | 17436 | 0.2095 |
| 0.204 | 13.0 | 18889 | 0.2096 |
| 0.1872 | 14.0 | 20342 | 0.2094 |
| 0.1879 | 15.0 | 21795 | 0.2094 |
Framework versions
- PEFT 0.9.1.dev0
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-small