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openai/whisper-small

This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2195
  • Wer: 19.56

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: 2
  • eval_batch_size: 1
  • 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: 10000
  • mixed_precision_training: Native AMP

Training results

Epoch Step Wer
0.1 1000 43.61
0.2 2000 36.79
0.3 3000 33.05
0.4 4000 29.53
0.5 5000 26.01
0.6 6000 23.44
0.7 7000 22.22
0.8 8000 21.88
0.9 9000 20.53
1.0 10000 19.56

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train AigizK/whisper-medium-ba

Evaluation results