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openai/whisper-medium

This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1594
  • Wer: 21.8343

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: 32
  • eval_batch_size: 32
  • 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
0.0269 5.0 500 0.1069 118.0302
0.0049 10.01 1000 0.1263 135.2788
0.0009 15.01 1500 0.1355 94.5731
0.0001 20.01 2000 0.1413 7.5188
0.0001 25.01 2500 0.1515 7.2508
0.0001 30.02 3000 0.1568 24.8493
0.0 35.02 3500 0.1588 22.1470
0.0 40.02 4000 0.1594 21.8343

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.9.1.dev0
  • Tokenizers 0.13.2
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Evaluation results