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Whisper Base Noisy

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

  • Loss: 1.4454
  • Wer: 59.3212

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: 4000

Training results

Training Loss Epoch Step Validation Loss Wer
0.3125 3.19 1000 1.0918 56.8476
0.0585 6.39 2000 1.2650 58.9703
0.0153 9.58 3000 1.3946 58.3412
0.0066 12.78 4000 1.4454 59.3212

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train alxfng/whisper-noisy

Evaluation results