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Whisper Small et - Common Voice+FLEURS

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

  • Loss: 0.8754
  • Wer: 42.4844

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: 64
  • eval_batch_size: 32
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0094 10.0 1000 0.7125 43.4085
0.0024 20.01 2000 0.7960 42.1795
0.0012 30.01 3000 0.8237 41.8961
0.0006 40.02 4000 0.8627 41.7853
0.0004 51.0 5000 0.8754 42.4844

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 rristo/whisper-small-et-cv-fleurs

Evaluation results