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whisper-large-marathi

This model is a fine-tuned version of openai/whisper-large on the Common Voice 17 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1845
  • Wer Ortho: 32.4713
  • Wer: 11.9958

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: 12
  • 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: 20
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1771 1.0 250 0.2041 36.0371 13.7851
0.0806 2.0 500 0.1845 32.4713 11.9958

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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Evaluation results