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Whisper Large v3 Ai - Nurlan Salahaddinov

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Wer: 1.1952

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: 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
0.0001 40.0 1000 0.0001 1.1952
0.0 80.0 2000 0.0000 1.1952
0.0 120.0 3000 0.0000 1.1952
0.0 160.0 4000 0.0000 1.1952
0.0 200.0 5000 0.0000 1.1952

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train nsalahaddinov/whisper-large-v3-az

Evaluation results