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whisper-large-v3-pt-cv16-cuda

This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_16_0 pt dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1325
  • Wer: 0.9999

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-06
  • train_batch_size: 8
  • 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: 2000
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.199 0.26 1000 0.1563 0.1124
0.1654 0.52 2000 0.1500 0.1052
0.1794 0.77 3000 0.1379 0.0997
0.0821 1.03 4000 0.1321 1.0007
0.1292 1.29 5000 0.1325 0.9999

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.2.0.dev20231212
  • Datasets 2.15.1.dev0
  • Tokenizers 0.15.0
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Dataset used to train fsicoli/whisper-large-v3-pt-cv16-cuda

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Evaluation results