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Whisper Large v2 TR

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2089
  • Wer: 11.4778

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1641 1.0 3147 0.1899 11.9306
0.0904 2.0 6294 0.1904 11.3074
0.0547 3.0 9441 0.2089 11.4778

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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Evaluation results