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Whisper Large V3 pl - Chee Li

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1865
  • Wer: 614.9727

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1328 0.6439 1000 0.2206 275.0400
0.0517 1.2878 2000 0.2183 668.6775
0.0501 1.9317 3000 0.1740 468.4439
0.022 2.5757 4000 0.1865 614.9727

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Dataset used to train liqi03/whisper-large-v3-pl-finetuned

Evaluation results