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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:

• mozilla-foundation/common_voice_11_0 (test)

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