Whisper Medium 1000 orders Eleven Labs SSD superU

This model is a fine-tuned version of shreyasdesaisuperU/whisper-medium-attempt2-1000-orders on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0128
  • Wer: 0.8606

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0668 0.4032 100 0.0388 17.3838
0.0142 0.8065 200 0.0061 11.3597
0.0075 1.2097 300 0.0075 9.6386
0.0073 1.6129 400 0.0104 7.7453
0.0087 2.0161 500 0.0125 2.9260
0.0046 2.4194 600 0.0080 1.5491
0.0087 2.8226 700 0.0039 1.7212
0.0066 3.2258 800 0.0042 1.3769
0.0032 3.6290 900 0.0095 1.0327
0.0027 4.0323 1000 0.0114 1.5491
0.0021 4.4355 1100 0.0099 1.7212
0.0039 4.8387 1200 0.0121 1.8933
0.0017 5.2419 1300 0.0126 1.3769
0.0033 5.6452 1400 0.0093 1.8933
0.0037 6.0484 1500 0.0126 1.2048
0.0013 6.4516 1600 0.0090 1.2048
0.0014 6.8548 1700 0.0102 1.2048
0.0002 7.2581 1800 0.0115 0.8606
0.0005 7.6613 1900 0.0142 1.0327
0.0002 8.0645 2000 0.0128 0.8606

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.2.2+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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