Edit model card

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:

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
Downloads last month
4
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Jasper881108/whisper-medium-zh

Evaluation results