--- 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: 0.0089 - Wer: 0.0818 - Cer: 0.0316 ## 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-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - 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: 25 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 0.0013 | 1.0 | 157 | 0.0090 | 0.0833 | 0.0301 | | 0.0019 | 2.0 | 314 | 0.0096 | 0.0894 | 0.0309 | | 0.001 | 3.0 | 471 | 0.0107 | 0.0968 | 0.0353 | | 0.0015 | 4.0 | 628 | 0.0114 | 0.1035 | 0.0382 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0