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whisper_finetune

This model is a fine-tuned version of openai/whisper-large-v3 on the aihub_100000 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4933
  • Cer: 6.9924
  • Wer: 28.6257

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-08
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer
0.6435 0.14 1000 0.6061 7.0810 29.1317
0.515 0.28 2000 0.4933 6.9924 28.6257

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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