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Whisper Base LoRA tuned zh-TW

DEMO LINK: https://4e766dca651b881c9b.gradio.live

This model is a fine-tuned version with PEFT-LoRA of openai/whisper-base on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3839
  • CER: 22.13% :(

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
0.3981 1.0 1453 0.4017
0.4016 2.0 2906 0.3960
0.3543 3.0 4359 0.3933
0.3638 4.0 5812 0.3905
0.3953 5.0 7265 0.3895
0.377 6.0 8718 0.3879
0.3646 7.0 10171 0.3869
0.3592 8.0 11624 0.3860
0.3324 9.0 13077 0.3853
0.3818 10.0 14530 0.3848
0.3107 11.0 15983 0.3844
0.3473 12.0 17436 0.3844
0.3684 13.0 18889 0.3845
0.3886 14.0 20342 0.3841
0.3652 15.0 21795 0.3839

Framework versions

  • PEFT 0.9.1.dev0
  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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