--- 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: 0.0562 - Wer: 10.7169 ## 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: 32 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.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: 50 - training_steps: 500 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:-------:| | 0.5008 | 0.5405 | 100 | 0.1965 | 12.0203 | | 0.1034 | 1.0811 | 200 | 0.0870 | 12.2616 | | 0.0563 | 1.6216 | 300 | 0.0642 | 8.3514 | | 0.0238 | 2.1622 | 400 | 0.0610 | 11.6341 | | 0.0129 | 2.7027 | 500 | 0.0562 | 10.7169 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cu118 - Datasets 3.3.1 - Tokenizers 0.21.0