| | --- |
| | language: |
| | - de |
| | license: apache-2.0 |
| | base_model: openai/whisper-small |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - rmacek/common_voice_zib2 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Small ZIB2 |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: ZIB2 Common Voice |
| | type: rmacek/common_voice_zib2 |
| | args: 'config: de, split: test' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 28.93835616438356 |
| | --- |
| | |
| | <!-- 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 ZIB2 |
| |
|
| | 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: 0.3366 |
| | - Wer: 28.9384 |
| |
|
| | ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - training_steps: 1000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | | 0.2391 | 10.0 | 100 | 0.2837 | 33.5616 | |
| | | 0.0035 | 20.0 | 200 | 0.2701 | 27.7397 | |
| | | 0.0012 | 30.0 | 300 | 0.2847 | 27.5685 | |
| | | 0.0006 | 40.0 | 400 | 0.2990 | 27.9110 | |
| | | 0.0004 | 50.0 | 500 | 0.3118 | 28.5959 | |
| | | 0.0003 | 60.0 | 600 | 0.3221 | 28.5959 | |
| | | 0.0002 | 70.0 | 700 | 0.3287 | 28.7671 | |
| | | 0.0002 | 80.0 | 800 | 0.3333 | 28.9384 | |
| | | 0.0002 | 90.0 | 900 | 0.3357 | 28.9384 | |
| | | 0.0002 | 100.0 | 1000 | 0.3366 | 28.9384 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
