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study0703

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

  • Loss: 0.1988
  • Cer: 6.6313

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: 8
  • seed: 42
  • 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 Cer
0.004 9.6154 1000 0.1731 6.3102
0.0007 19.2308 2000 0.1849 6.3584
0.0004 28.8462 3000 0.1921 6.4226
0.0003 38.4615 4000 0.1968 6.5992
0.0002 48.0769 5000 0.1988 6.6313

Framework versions

  • Transformers 4.43.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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