whisper-large-odiya

This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2808
  • Wer Ortho: 45.8771
  • Wer: 18.4527

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: 16
  • 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: 1000

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0019 9.71 500 0.2362 45.4898 19.3002
0.0001 19.42 1000 0.2808 45.8771 18.4527

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Dataset used to train Apocalypse-19/whisper-large-odiya

Evaluation results