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Whisper Base EN

This model is a fine-tuned version of openai/whisper-medium.en on the ADLINK dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0017
  • Wer: 1.3384

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: 8
  • 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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.7899 4.1667 100 2.3530 21.4149
0.8377 8.3333 200 0.7500 4.2065
0.0599 12.5 300 0.0394 1.9120
0.0163 16.6667 400 0.0151 2.1033
0.0068 20.8333 500 0.0023 1.1472
0.0031 25.0 600 0.0018 1.3384
0.0027 29.1667 700 0.0023 1.3384
0.0018 33.3333 800 0.0020 1.3384
0.003 37.5 900 0.0017 1.3384
0.0009 41.6667 1000 0.0017 1.3384

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0a0+ebedce2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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