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whisper-small-test

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4846
  • Wer: 30.9001

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: constant_with_warmup
  • lr_scheduler_warmup_steps: 500
  • training_steps: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5133 0.64 500 0.5562 38.3826
0.3764 1.28 1000 0.4754 34.1921
0.3501 1.92 1500 0.4554 32.8509
0.222 2.55 2000 0.4399 32.3844
0.1283 3.19 2500 0.4440 32.0081
0.1575 3.83 3000 0.4295 31.8225
0.1205 4.47 3500 0.4410 31.0459
0.0992 5.11 4000 0.4505 31.1042
0.0941 5.75 4500 0.4551 30.8498
0.0627 6.39 5000 0.4696 31.5999
0.0652 7.02 5500 0.4761 31.8013
0.0573 7.66 6000 0.4846 30.9001

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.1+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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