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whisper_large

This model is a fine-tuned version of openai/whisper-large on the MAICON2023_noise dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2609
  • Cer: 27.9801

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: 4
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
0.6254 0.36 1000 0.5211 39.0406
0.3894 0.71 2000 0.3733 23.1574
0.0932 1.07 3000 0.2990 24.4794
0.0952 1.43 4000 0.2609 27.9801

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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