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Whisper Small PT with Common Voice 11

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3487
  • Wer: 14.3802

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 10000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1202 0.88 1000 0.2225 15.5847
0.1024 1.76 2000 0.2160 15.0651
0.0832 2.64 3000 0.2259 15.0923
0.0081 3.51 4000 0.2519 14.7345
0.0387 4.39 5000 0.2718 14.7311
0.0039 5.27 6000 0.3031 14.5914
0.001 6.15 7000 0.3238 14.5710
0.0007 7.03 8000 0.3285 14.5113
0.0009 7.91 9000 0.3467 14.3580
0.0008 8.79 10000 0.3487 14.3802

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.12.1
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Dataset used to train lgris/whisper-small-cv11-pt

Evaluation results