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whisper-large-v3-Urdu-Version1

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

  • Loss: 0.3244
  • Wer: 20.6725

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: 8
  • 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: 1000
  • training_steps: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3271 6.7340 2000 0.3375 21.5842
0.3107 13.4680 4000 0.3244 20.9093
0.2797 20.2020 6000 0.3205 20.8383
0.2639 26.9360 8000 0.3202 20.5778
0.2529 33.6700 10000 0.3216 20.7909
0.26 40.4040 12000 0.3230 20.6843
0.2485 47.1380 14000 0.3244 20.6725

Framework versions

  • PEFT 0.12.1.dev0
  • Transformers 4.45.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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