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whisper-tiny-en-US

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6166
  • Wer Ortho: 0.3504
  • Wer: 0.3536

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.7658 1.7857 50 0.5871 0.3948 0.3932
0.2602 3.5714 100 0.4866 0.3504 0.3501
0.0796 5.3571 150 0.5121 0.3424 0.3453
0.0316 7.1429 200 0.5443 0.3374 0.3418
0.0116 8.9286 250 0.5672 0.3202 0.3253
0.0034 10.7143 300 0.5966 0.3529 0.3566
0.0026 12.5 350 0.6046 0.3541 0.3583
0.002 14.2857 400 0.6098 0.3498 0.3536
0.002 16.0714 450 0.6146 0.3510 0.3542
0.002 17.8571 500 0.6166 0.3504 0.3536

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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Dataset used to train AlirezaTirehkar/whisper-tiny-en-US

Evaluation results