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metadata
library_name: transformers
language:
  - ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-medium-ur
tags:
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Medium Ur - Muhammad Abdullah on Fleurs
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Fleurs Urdu
          type: google/fleurs
          config: ur_pk
          split: test
          args: 'config: ur_pk, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 22.839213829031493

Whisper Medium Ur - Muhammad Abdullah on Fleurs

This model is a fine-tuned version of GogetaBlueMUI/whisper-medium-ur on the Fleurs Urdu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3747
  • Wer: 22.8392

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 60
  • training_steps: 300
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3288 0.7576 100 0.3701 23.7272
0.1527 1.5152 200 0.3769 23.5496
0.0874 2.2727 300 0.3747 22.8392

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.3.2
  • Tokenizers 0.21.0