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Whisper large - tuned

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

  • Loss: 0.1992
  • Wer: 156.8649

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: 9375
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0864 1.6 1000 0.1155 165.5135
0.0291 3.2 2000 0.1192 268.0360
0.0196 4.8 3000 0.1317 217.9820
0.0024 6.4 4000 0.1583 136.1802
0.0012 8.0 5000 0.1708 136.3604
0.0004 9.6 6000 0.1841 128.7207
0.0009 11.2 7000 0.1831 169.8739
0.0003 12.8 8000 0.1885 158.7387
0.0001 14.4 9000 0.1992 156.8649

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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Finetuned from

Dataset used to train whitefox123/whisper-large-ar5

Evaluation results