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Whisper Large Mongolian

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4028
  • Wer: 37.2336

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: 4
  • 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: 50
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3446 0.99 1000 0.4391 51.4572
0.1481 1.98 2000 0.3765 42.2412
0.076 2.97 3000 0.3830 39.0822
0.0149 3.96 4000 0.4028 37.2336

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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Evaluation results