--- library_name: transformers language: - ar license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer metrics: - wer model-index: - name: Whisper tiny AR - BH results: [] --- # Whisper tiny AR - BH This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set: - Loss: 0.0070 - Wer: 0.0780 - Cer: 0.0312 ## 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: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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 - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-------:|:----:|:---------------:|:------:|:------:| | 0.0099 | 1.0 | 157 | 0.0075 | 0.0746 | 0.0300 | | 0.0068 | 2.0 | 314 | 0.0069 | 0.0682 | 0.0272 | | 0.0054 | 3.0 | 471 | 0.0068 | 0.0700 | 0.0278 | | 0.0043 | 4.0 | 628 | 0.0070 | 0.0726 | 0.0283 | | 0.0031 | 5.0 | 785 | 0.0074 | 0.0726 | 0.0287 | | 0.002 | 6.0 | 942 | 0.0082 | 0.0706 | 0.0285 | | 0.0015 | 7.0 | 1099 | 0.0089 | 0.0758 | 0.0381 | | 0.0005 | 8.0 | 1256 | 0.0096 | 0.0767 | 0.0479 | | 0.0001 | 9.0 | 1413 | 0.0100 | 0.0767 | 0.0385 | | 0.0002 | 10.0 | 1570 | 0.0104 | 0.0746 | 0.0474 | | 0.0 | 11.0 | 1727 | 0.0107 | 0.0751 | 0.0474 | | 0.0 | 12.0 | 1884 | 0.0109 | 0.0764 | 0.0482 | | 0.0 | 13.0 | 2041 | 0.0112 | 0.0746 | 0.0479 | | 0.0 | 14.0 | 2198 | 0.0113 | 0.0749 | 0.0488 | | 0.0 | 15.0 | 2355 | 0.0116 | 0.0767 | 0.0495 | | 0.0 | 16.0 | 2512 | 0.0119 | 0.0764 | 0.0488 | | 0.0 | 17.0 | 2669 | 0.0121 | 0.0757 | 0.0487 | | 0.0 | 18.0 | 2826 | 0.0122 | 0.0753 | 0.0489 | | 0.0 | 19.0 | 2983 | 0.0127 | 0.0766 | 0.0390 | | 0.0 | 19.8768 | 3120 | 0.0124 | 0.0755 | 0.0493 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0