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./3479

This model is a fine-tuned version of openai/whisper-large-v3 on the 3479 clips dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5117
  • Wer Ortho: 27.4535
  • Wer: 19.3463

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-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: 200
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.8906 0.5109 100 0.6318 33.6218 25.1010
0.6428 1.0217 200 0.5620 30.8415 22.5971
0.5279 1.5326 300 0.5435 32.0107 23.8886
0.4958 2.0434 400 0.5244 30.0037 21.7800
0.4238 2.5543 500 0.5171 28.4662 20.2337
0.4016 3.0651 600 0.5132 28.0980 19.8647
0.3562 3.5760 700 0.5132 27.6100 19.7505
0.3467 4.0868 800 0.5103 27.1037 19.0828
0.308 4.5977 900 0.5117 27.3246 19.1618
0.3174 5.1086 1000 0.5117 27.4535 19.3463

Framework versions

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