--- library_name: transformers language: - ps base_model: ihanif/whisper-small-tunning-v2 tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Small PS - CV20-1 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 args: 'config: ps, split: test' metrics: - name: Wer type: wer value: 89.79300499643112 --- # Whisper Small PS - CV20-1 This model is a fine-tuned version of [ihanif/whisper-small-tunning-v2](https://huggingface.co/ihanif/whisper-small-tunning-v2) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.6103 - Wer Ortho: 91.8037 - Wer: 89.7930 ## 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: 64 - eval_batch_size: 64 - 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_ratio: 0.1 - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| | 2.6485 | 1.8868 | 100 | 0.6103 | 91.8037 | 89.7930 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0