--- library_name: transformers language: - fr license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - IndabaxSenegal/asr-wolof-dataset metrics: - wer model-index: - name: Whisper Small WO - Team results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: ASR Wolof Dataset type: IndabaxSenegal/asr-wolof-dataset args: 'config: wo, split: test' metrics: - name: Wer type: wer value: 78.44373118690858 --- # Whisper Small WO - Team This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ASR Wolof Dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.1726 - Wer: 78.4437 ## 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: 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: 500 - training_steps: 4000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.0965 | 1.5408 | 1000 | 0.1751 | 83.2067 | | 0.0406 | 3.0817 | 2000 | 0.1761 | 78.6749 | | 0.0192 | 4.6225 | 3000 | 0.1772 | 78.8612 | | 0.0037 | 6.1633 | 4000 | 0.1726 | 78.4437 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.4.0 - Datasets 3.1.0 - Tokenizers 0.20.0