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Whisper Small En - Whisper with ATCOSIM

This model is a fine-tuned version of openai/whisper-small on the Air Traffic Control Simulation Speech corpus dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0487
  • Wer: 1.4442

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
0.0014 2.09 1000 0.0482 1.5944
0.0001 4.18 2000 0.0491 1.5944
0.0 6.28 3000 0.0480 1.4266
0.0 8.37 4000 0.0487 1.4442

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Finetuned from

Dataset used to train youngsangroh/whisper-small-finetuned-atcosim-corpus

Evaluation results

  • Wer on Air Traffic Control Simulation Speech corpus
    self-reported
    1.444