Whisper Medium TW
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 dataset.
Training and evaluation data
Training:
- mozilla-foundation/common_voice_11_0 (train+validation)
Evaluation:
Training procedure
- Datasets were augmented using audiomentations via PitchShift, TimeStretch, Gain, AddGaussianNoise transformations at
p=0.3. - A space is added between each Chinese character, as demonstrated in the original paper. Effectively, WER == CER in this case.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- gradient_accumulation_steps: 32
- optimizer: Adam
- generation_max_length: 225,
- warmup_steps: 200
- max_steps: 2000,
- fp16: True,
- evaluation_strategy: "steps",
Framework versions
- Transformers 4.27.1
- Pytorch 2.0.1+cu120
- Datasets 2.13.1
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Dataset used to train Jasper881108/whisper-medium-zh
Evaluation results
- WER on mozilla-foundation/common_voice_11_0test set self-reported7.380