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wav2vec2-large-xlsr-53-ur-cv13

This model is a fine-tuned version of Talha/URDU-ASR on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4323
  • Wer: 0.3988
  • Cer: 0.1932

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.8043 1.46 250 0.5256 0.4023 0.1949
0.5435 2.92 500 0.4381 0.3965 0.1961
0.4827 4.39 750 0.4323 0.3988 0.1932

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Evaluation results