Whisper Medium Medical

--- library_name: transformers license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-medium-medical results: [] --- # whisper-medium-medical This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2889 - Wer: 0.1281 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_BNB 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: 100 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 2.4747 | 1.0 | 102 | 0.3153 | 0.1621 | | 1.4045 | 2.0 | 204 | 0.2641 | 0.1341 | | 0.6465 | 3.0 | 306 | 0.2671 | 0.1321 | | 0.2759 | 4.0 | 408 | 0.2727 | 0.1278 | | 0.1574 | 5.0 | 510 | 0.2889 | 0.1281 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 2.19.0 - Tokenizers 0.22.2