--- 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: 0.0088 - Wer: 0.1392 - Cer: 0.0529 ## 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: 5e-06 - 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: 15 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 0.0087 | 1.0 | 313 | 0.0090 | 0.1752 | 0.0620 | | 0.0069 | 2.0 | 626 | 0.0088 | 0.1385 | 0.0468 | | 0.007 | 3.0 | 939 | 0.0087 | 0.1595 | 0.0576 | | 0.0052 | 4.0 | 1252 | 0.0088 | 0.1329 | 0.0420 | | 0.0055 | 5.0 | 1565 | 0.0086 | 0.1571 | 0.0525 | | 0.004 | 6.0 | 1878 | 0.0086 | 0.1609 | 0.0575 | | 0.0034 | 7.0 | 2191 | 0.0089 | 0.1372 | 0.0447 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0