Whisper Medium Full Clinical R16

--- library_name: transformers license: apache-2.0 base_model: openai/whisper-medium tags: - generated_from_trainer datasets: - afrispeech-200 metrics: - wer model-index: - name: whisper-medium-full-clinical-r16 results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: afrispeech-200 type: afrispeech-200 config: all split: None args: all metrics: - name: Wer type: wer value: 22.403991182271728 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # whisper-medium-full-clinical-r16 This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the afrispeech-200 dataset. It achieves the following results on the evaluation set: - Loss: 0.7557 - Wer: 22.4040 - Cer: 8.9223 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 200 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:| | 2.5732 | 1.1047 | 2500 | 0.4727 | 26.4687 | 12.7305 | | 1.4199 | 2.2095 | 5000 | 0.4792 | 24.9217 | 11.0376 | | 0.5931 | 3.3142 | 7500 | 0.5210 | 23.6145 | 9.9791 | | 0.3973 | 4.4189 | 10000 | 0.5586 | 24.2720 | 10.2508 | | 0.1234 | 5.5237 | 12500 | 0.6029 | 23.0924 | 9.3290 | | 0.0623 | 6.6284 | 15000 | 0.6551 | 22.9377 | 9.1811 | | 0.0322 | 7.7331 | 17500 | 0.6905 | 22.4311 | 9.0467 | | 0.0251 | 8.8379 | 20000 | 0.7327 | 22.5123 | 8.9581 | | 0.0127 | 9.9426 | 22500 | 0.7556 | 22.4233 | 8.9253 | | 0.0090 | 10.0 | 22630 | 0.7557 | 22.4040 | 8.9223 | ### Framework versions - Transformers 5.5.4 - Pytorch 2.11.0+cu130 - Datasets 2.1...