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Whisper small it - m1

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

  • Loss: 0.2185
  • Wer: 8.1873

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: 8
  • 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: 2500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0744 2.6316 500 0.1838 10.7450
0.006 5.2632 1000 0.2006 8.1145
0.0022 7.8947 1500 0.2094 8.0951
0.0017 10.5263 2000 0.2159 8.0466
0.0014 13.1579 2500 0.2185 8.1873

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train Berly00/whisper-small-italian-1

Evaluation results