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: 0.1346
  • Wer: 217.9099

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: 3125
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0843 1.6 1000 0.1141 248.9730
0.024 3.2 2000 0.1194 274.9189
0.0108 4.8 3000 0.1346 217.9099

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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Dataset used to train whitefox123/whisper-large-ar6

Evaluation results