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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: 0.5021
  • Wer: 11.9280

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
0.3007 1.01 500 0.3027 12.4842
0.0962 2.02 1000 0.3147 11.9450
0.0409 3.03 1500 0.3528 12.9437
0.0298 4.04 2000 0.4015 11.7048
0.0114 5.06 2500 0.4310 12.3353
0.0034 6.07 3000 0.4666 11.6630
0.0014 7.08 3500 0.5117 11.7505
0.0016 8.09 4000 0.5021 11.9280

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