FULL6

This model is a fine-tuned version of openai/whisper-large-v3 on the 9651 FULL-2024-12-01 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3740
  • Wer Ortho: 20.5948
  • Wer: 14.5676

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-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 300
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.646 0.3683 200 0.4534 25.1768 18.6441
0.5098 0.7366 400 0.4155 24.7355 18.4413
0.4491 1.1050 600 0.3936 21.8793 15.6599
0.3674 1.4733 800 0.3875 21.7736 15.4860
0.365 1.8416 1000 0.3765 21.2869 15.1644
0.3171 2.2099 1200 0.3779 21.1358 15.0978
0.2886 2.5783 1400 0.3755 20.7610 14.6661
0.2871 2.9466 1600 0.3689 20.6009 14.6023
0.2395 3.3149 1800 0.3752 20.6825 14.8110
0.2444 3.6832 2000 0.3740 20.5948 14.5676

Framework versions

  • Transformers 4.44.0
  • Pytorch 1.13.1+cu117
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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