--- language: - de license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: openai/whisper-small datasets: - rmacek/ORF-whisper-small metrics: - wer model-index: - name: Whisper ORF Bundeslaender results: - task: type: automatic-speech-recognition name: Automatic Speech Recognition dataset: name: ZIB2 Common Voice type: rmacek/ORF-whisper-small args: 'config: de, split: test' metrics: - type: wer value: 27.268895060503866 name: Wer --- # Whisper ORF Bundeslaender This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ZIB2 Common Voice dataset. It achieves the following results on the evaluation set: - Loss: 0.7038 - Wer: 27.2689 ## 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: 0.0001 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 8000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:----:|:---------------:|:-------:| | 0.4896 | 1.7153 | 1000 | 0.6019 | 26.6961 | | 0.3559 | 3.4305 | 2000 | 0.6038 | 26.6192 | | 0.259 | 5.1458 | 3000 | 0.6216 | 33.8450 | | 0.3272 | 6.8611 | 4000 | 0.6382 | 27.0730 | | 0.2413 | 8.5763 | 5000 | 0.6704 | 31.3207 | | 0.1691 | 10.2916 | 6000 | 0.6922 | 27.2466 | | 0.1702 | 12.0069 | 7000 | 0.7008 | 27.3284 | | 0.1726 | 13.7221 | 8000 | 0.7038 | 27.2689 | ### Framework versions - PEFT 0.10.1.dev0 - Transformers 4.40.0 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1