--- datasets: - mozilla-foundation/common_voice_11_0 language: - ur metrics: - wer library_name: transformers license: apache-2.0 tags: - hf-asr-leaderboard - generated_from_trainer model-index: - name: Whisper Medium Urdu - Hassaan Butt results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: fleurs type: mozilla-foundation/common_voice_11_0 config: ur split: test args: 'config: ps, split: test' metrics: - name: Wer type: wer value: 32.0 --- # Whisper Medium Urdu - Hassaan Butt This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common voice dataset. It achieves the following results on the evaluation set: - Wer: 32.0 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 3000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 0.283800 | 2.92 | 1000 | 0.466280 | 51.433879 | | 0.090300 | 5.85 | 2000 | 0.448847 | 33.646813 | | 0.036666 | 8.77 | 3000 | 0.420809 | 32.035004 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.11.0+cu113 - Datasets 11.0 - Tokenizers 0.13.2