Whisper Large Ur

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 14.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5723
  • Wer: 32.2031

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: 64
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0147 9.06 1000 0.5723 32.2031

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Evaluation results