Whisper Large v3 Fine-Tuned Finnish

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2178
  • Wer: 23.707

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • lr_scheduler_kwargs = { 'lr_end': 1e-07 }
  • training_steps: 800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6193 0.21 50 0.2905 29.1920
0.3171 0.84 200 0.3 27.02
0.1224 1.68 400 0.2906 28.115
0.041 2.53 600 0.2477 25.179
0.0098 3.37 800 0.2178 23.707

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Dataset used to train enakilci/whisper-large-v3-fi-800steps-8batch-2grad_steps-5e-05-1e-07lr-poly

Evaluation results