Whisper Small zh-TW - hanson92828
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2087
- Wer: 203.2213
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0974 | 1.3263 | 1000 | 0.1997 | 167.3042 |
0.0218 | 2.6525 | 2000 | 0.1987 | 228.9309 |
0.0094 | 3.9788 | 3000 | 0.2022 | 221.2603 |
0.0025 | 5.3050 | 4000 | 0.2087 | 203.2213 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.2
- Tokenizers 0.20.1
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openai/whisper-small