--- library_name: transformers language: - ur license: apache-2.0 base_model: GogetaBlueMUI/whisper-medium-ur-jalandhary tags: - generated_from_trainer datasets: - mirfan899/jalandhary_asr metrics: - wer model-index: - name: Whisper Medium Ur - Jalandhary ASR Fine-Tuned results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Jalandhary ASR type: mirfan899/jalandhary_asr args: 'split: test' metrics: - name: Wer type: wer value: 19.807797769827385 --- # Whisper Medium Ur - Jalandhary ASR Fine-Tuned This model is a fine-tuned version of [GogetaBlueMUI/whisper-medium-ur-jalandhary](https://huggingface.co/GogetaBlueMUI/whisper-medium-ur-jalandhary) on the Jalandhary ASR dataset. It achieves the following results on the evaluation set: - Loss: 0.1012 - Wer: 19.8078 ## 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-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - 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: 300 - training_steps: 2400 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.1097 | 0.5831 | 600 | 0.1066 | 18.6509 | | 0.0664 | 1.1662 | 1200 | 0.1020 | 19.1575 | | 0.0821 | 1.7493 | 1800 | 0.1016 | 19.2725 | | 0.0567 | 2.3324 | 2400 | 0.1012 | 19.8078 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.5.1+cu121 - Datasets 3.3.2 - Tokenizers 0.21.0