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Whisper Large V2

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2953
  • Wer: 11.3276

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: 3e-05
  • train_batch_size: 12
  • 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: 20
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer
0.5452 0.4839 15 0.3714 23.2724
0.2911 0.9677 30 0.2866 18.6494
0.1304 1.4516 45 0.2713 13.6270
0.1196 1.9355 60 0.2595 12.7436
0.0595 2.4194 75 0.2615 11.8964
0.043 2.9032 90 0.2700 13.0098
0.0229 3.3871 105 0.2854 15.4786
0.0176 3.8710 120 0.2747 12.9856
0.0101 4.3548 135 0.2882 11.1340
0.0069 4.8387 150 0.2953 11.3276

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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