| --- |
| library_name: transformers |
| language: |
| - de |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - automatic-speech-recognition |
| - generated_from_trainer |
| datasets: |
| - openai/whisper-small |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small DE - Maximilian Kenfenheuer |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17.0 |
| type: openai/whisper-small |
| config: de |
| split: test |
| args: 'config: de, split: validated' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 7.5439641517863185 |
| --- |
| |
| <!-- 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 Small DE - Maximilian Kenfenheuer |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1231 |
| - Wer: 7.5440 |
|
|
| ## 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: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use 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: 500 |
| - training_steps: 4000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.1911 | 0.25 | 1000 | 0.1567 | 9.4088 | |
| | 0.1959 | 0.5 | 2000 | 0.1382 | 8.5261 | |
| | 0.1843 | 0.75 | 3000 | 0.1285 | 7.8513 | |
| | 0.2134 | 1.0 | 4000 | 0.1231 | 7.5440 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
