README.md

metadata

library_name: transformers
language:
  - ur
license: apache-2.0
base_model: GogetaBlueMUI/whisper-small-ur
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Small Urdu V2 - Muhammad Abdullah
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13.0
          type: mozilla-foundation/common_voice_13_0
          config: ur
          split: test
          args: 'config: ur, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 35.42311262376238

Whisper Small Urdu V2 - Muhammad Abdullah

This model is a fine-tuned version of GogetaBlueMUI/whisper-small-ur on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.7436
• Wer: 35.4231

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: 16
• 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: 500
• training_steps: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.068	1.9305	500	0.6670	37.1751
0.0182	3.8610	1000	0.7094	35.9684
0.0032	5.7915	1500	0.7436	35.4231

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.21.0