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Whisper Medium

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

  • Loss: 0.4874
  • Wer: 10.9375

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.2174 0.5714 100 1.9102 49.4792
0.2353 1.1429 200 0.3485 30.7292
0.1668 1.7143 300 0.7634 21.875
0.118 2.2857 400 0.6914 11.9792
0.0931 2.8571 500 0.5523 15.1042
0.0851 3.4286 600 0.6818 13.0208
0.0751 4.0 700 0.6348 11.9792
0.066 4.5714 800 0.6576 11.9792
0.0604 5.1429 900 0.4125 10.9375
0.0564 5.7143 1000 0.6815 10.9375
0.0499 6.2857 1100 0.4861 11.4583
0.0472 6.8571 1200 0.4874 10.9375

Framework versions

  • PEFT 0.12.0
  • Transformers 4.43.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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