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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: 0.3896
  • Wer: 200.1910

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
0.2328 0.12 500 0.2655 301.5949
0.1838 1.11 1000 0.2496 286.1977
0.1757 2.1 1500 0.2563 118.9213
0.0254 3.09 2000 0.2992 237.0841
0.0282 4.07 2500 0.3342 125.1999
0.0229 5.06 3000 0.3502 268.7414
0.0027 6.05 3500 0.3918 107.5536
0.003 7.03 4000 0.3896 200.1910

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