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metadata
library_name: transformers
language:
  - ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-medium-ur-jalandhary
tags:
  - generated_from_trainer
datasets:
  - mirfan899/jalandhary_asr
metrics:
  - wer
model-index:
  - name: Whisper Medium Ur - Jalandhary ASR Fine-Tuned
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Jalandhary ASR
          type: mirfan899/jalandhary_asr
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 19.807797769827385

Whisper Medium Ur - Jalandhary ASR Fine-Tuned

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

  • Loss: 0.1012
  • Wer: 19.8078

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • 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: 300
  • training_steps: 2400
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1097 0.5831 600 0.1066 18.6509
0.0664 1.1662 1200 0.1020 19.1575
0.0821 1.7493 1800 0.1016 19.2725
0.0567 2.3324 2400 0.1012 19.8078

Framework versions

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