README.md

metadata

language:
  - ur
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_7_0
metrics:
  - wer
model-index:
  - name: Whisper Small Ur - Bakht Ullah
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7.0
          type: mozilla-foundation/common_voice_7_0
          args: 'config: ur, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 47.34088927637315

Whisper Small Ur - Bakht Ullah

This model is a fine-tuned version of openai/whisper-small on the Common Voice 7.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.8930
• Wer: 47.3409

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 300
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6104	4.17	100	1.1037	163.3827
0.0242	8.33	200	0.8656	47.6024
0.0042	12.5	300	0.8930	47.3409

Framework versions

• Transformers 4.25.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.6.1
• Tokenizers 0.13.2