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: 0.3622
  • Wer: 10.6091

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
0.5314 0.12 500 0.2762 13.2758
0.1619 1.09 1000 0.2541 11.6909
0.069 2.05 1500 0.2768 10.2892
0.0756 3.02 2000 0.2756 11.6142
0.0324 3.14 2500 0.2961 11.1800
0.0171 4.11 3000 0.3322 11.1689
0.0046 5.07 3500 0.3653 10.5858
0.0091 6.03 4000 0.3622 10.6091

Framework versions

  • Transformers 4.29.0
  • Pytorch 1.14.0a0+44dac51
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Evaluation results