--- license: apache-2.0 tags: - whisper-event - generated_from_trainer datasets: - kul-speech-lab/CGN metrics: - wer model-index: - name: Whisper Medium CGN results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: kul-speech-lab/CGN type: kul-speech-lab/CGN config: cgn-dev.py split: test metrics: - name: Wer type: wer value: 10.727751271110364 --- # Whisper Medium CGN This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the kul-speech-lab/CGN dataset. It achieves the following results on the evaluation set: - Loss: 0.2639 - Wer: 10.7278 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 64 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 15000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:-------:| | 0.1116 | 1.01 | 1000 | 0.2978 | 15.2127 | | 0.0786 | 2.03 | 2000 | 0.2842 | 13.4852 | | 0.2042 | 3.04 | 3000 | 0.2656 | 13.3590 | | 0.1183 | 4.05 | 4000 | 0.2667 | 12.6977 | | 0.0584 | 6.01 | 5000 | 0.2604 | 12.0993 | | 0.0126 | 7.02 | 6000 | 0.2776 | 12.1477 | | 0.0837 | 8.04 | 7000 | 0.2541 | 11.9397 | | 0.0229 | 9.05 | 8000 | 0.2663 | 11.3221 | | 0.042 | 11.01 | 9000 | 0.2549 | 11.4863 | | 0.0075 | 12.02 | 10000 | 0.2775 | 11.0780 | | 0.008 | 13.03 | 11000 | 0.2499 | 10.9759 | | 0.0739 | 14.05 | 12000 | 0.2308 | 10.9441 | | 0.0379 | 16.01 | 13000 | 0.2423 | 10.7926 | | 0.02 | 17.02 | 14000 | 0.2629 | 10.7699 | | 0.0111 | 18.03 | 15000 | 0.2639 | 10.7278 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.13.0 - Datasets 2.7.1.dev0 - Tokenizers 0.13.2 Whisper medium model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN).