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Whisper Small En - Whisper with atco2-asr-atcosim

This model is a fine-tuned version of openai/whisper-small on the This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM. dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0010
  • Wer: 0.0258

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
0.0637 1.9763 1000 0.0962 7.4365
0.0154 3.9526 2000 0.0163 2.3972
0.002 5.9289 3000 0.0027 1.5015
0.0003 7.9051 4000 0.0010 0.0258

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Model size
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F32
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Finetuned from

Dataset used to train youngsangroh/whisper-small-finetuned-atco2-asr-atcosim

Evaluation results

  • Wer on This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM.
    self-reported
    0.026