--- language: - ara license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer datasets: - AsemBadr/GP metrics: - wer model-index: - name: Whisper Small for Quran Recognition results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Quran_Reciters type: AsemBadr/GP config: default split: test args: 'config: default, split: train' metrics: - name: Wer type: wer value: 3.747636238610968 --- # Whisper Small for Quran Recognition This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Quran_Reciters dataset. It achieves the following results on the evaluation set: - Loss: 0.0193 - Wer: 3.7476 ## 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: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0264 | 1.62 | 500 | 0.0319 | 8.0110 | | 0.0012 | 3.24 | 1000 | 0.0228 | 5.5011 | | 0.0009 | 4.85 | 1500 | 0.0209 | 4.1258 | | 0.0003 | 6.47 | 2000 | 0.0185 | 3.7992 | | 0.0002 | 8.09 | 2500 | 0.0188 | 3.7820 | | 0.0001 | 9.71 | 3000 | 0.0191 | 3.7476 | | 0.0001 | 11.33 | 3500 | 0.0193 | 3.7133 | | 0.0 | 12.94 | 4000 | 0.0193 | 3.7476 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1