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medium

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

  • Loss: 0.4547
  • Wer: 11.8776
  • Cer: 7.0531
  • Wer Normalized: 11.8782

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: 32
  • eval_batch_size: 16
  • 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: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Wer Normalized
0.7386 1.7544 500 0.3919 9.6967 5.7829 9.6942
0.3228 3.5088 1000 0.4447 10.0253 6.0106 10.0254
0.1196 5.2632 1500 0.5873 10.2440 6.1735 10.2441

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.1.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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