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Whisper Medium New Train

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 18.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0204
  • Wer: 2.2783

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2733 0.4077 1000 0.2585 32.5924
0.1527 0.8153 2000 0.1246 16.7238
0.0655 1.2230 3000 0.0776 10.5668
0.0455 1.6307 4000 0.0514 6.7675
0.0162 2.0383 5000 0.0353 4.4772
0.0129 2.4460 6000 0.0274 3.4364
0.0117 2.8536 7000 0.0220 2.5110
0.0044 3.2613 8000 0.0204 2.2783

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.3.1
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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Dataset used to train meiiny00/whisper-medium-checkpoint-8000

Evaluation results