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whisper-large-nya

This model is a fine-tuned version of openai/whisper-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4712
  • Wer: 21.5239

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: 2.5e-05
  • train_batch_size: 8
  • eval_batch_size: 4
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2416 0.99 500 0.5146 34.7076
0.1343 1.97 1000 0.4138 28.1748
0.0792 2.96 1500 0.4268 31.3290
0.0372 3.94 2000 0.4256 32.8057
0.0246 4.93 2500 0.4354 22.0673
0.0097 5.92 3000 0.4532 25.1742
0.003 6.9 3500 0.4595 21.0396
0.0005 7.89 4000 0.4586 21.3113
0.0007 8.87 4500 0.4653 21.7129
0.0002 9.86 5000 0.4712 21.5239

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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