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Whisper da-nst

This model is a fine-tuned version of openai/whisper-medium on the common_voice_14_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7234
  • Wer: 35.3094

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0133 4.04 1000 0.6362 48.9279
0.0025 9.04 2000 0.6635 37.4731
0.0001 14.03 3000 0.6959 34.1296
0.0001 19.03 4000 0.7166 35.1821
0.0 24.03 5000 0.7234 35.3094

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.1
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