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whisper-medium-ln-ojpl-2

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

  • Loss: 1.1202
  • Wer Ortho: 35.8309
  • Wer: 0.2901

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.0172 23.19 1000 0.9966 41.9139 0.3407
0.0053 46.38 2000 1.0716 37.0920 0.2996
0.0034 69.57 3000 1.1329 36.0163 0.2850
0.0021 92.75 4000 1.1202 35.8309 0.2901

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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Evaluation results