whisper-tiny-ln-ojpl-2

This model is a fine-tuned version of openai/whisper-tiny on the BrainTheos/ojpl dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2661
  • Wer Ortho: 50.1855
  • Wer: 0.4352

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 2000

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1767 11.36 500 0.9122 52.1142 0.4579
0.0191 22.73 1000 1.0786 53.7463 0.4538
0.0059 34.09 1500 1.1891 53.2641 0.4766
0.0019 45.45 2000 1.2661 50.1855 0.4352

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.0+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Evaluation results