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Whisper Turbo - Chee Li

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

  • Loss: 0.2122
  • Wer: 16.5502

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
0.0128 5.0251 1000 0.2026 11.1336
0.0021 10.0503 2000 0.2049 14.8868
0.0003 15.0754 3000 0.2108 13.6427
0.0001 20.1005 4000 0.2122 16.5502

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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