FULL6

This model is a fine-tuned version of openai/whisper-large-v3 on the 9712 FULL-2024-10-24 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3684
  • Wer Ortho: 20.2615
  • Wer: 14.4085

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
0.6536 0.3661 200 0.4514 25.3730 18.9684
0.5136 0.7323 400 0.4055 22.8309 16.6362
0.4422 1.0984 600 0.3855 21.7595 15.9420
0.3691 1.4645 800 0.3767 22.0561 15.9885
0.3633 1.8307 1000 0.3694 21.1391 15.3002
0.3282 2.1968 1200 0.3701 21.1633 15.3641
0.284 2.5629 1400 0.3657 20.5429 14.6728
0.2819 2.9291 1600 0.3640 20.4431 14.6031
0.2449 3.2952 1800 0.3672 20.4067 14.5247
0.2382 3.6613 2000 0.3684 20.2615 14.4085

Framework versions

  • Transformers 4.45.1
  • Pytorch 1.13.1+cu117
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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