| --- |
| language: |
| - de |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_11_0 |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-tiny-german-V2-HanNeurAI |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 11.0 German shuffled 200k rows |
| type: mozilla-foundation/common_voice_11_0 |
| config: de |
| split: test |
| args: 'config: de, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 32.33273006844562 |
| --- |
| |
| <!-- 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-tiny-german-V2-HanNeurAI |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5818 |
| - Wer: 32.3327 |
|
|
| This fine-tuning model is part of my school project. |
| With limitation of my compute, I scale down the dataset from german common voice to shuffled 200k rows |
|
|
| Additional information can be found in this github: [HanCreation/Whisper-Tiny-German](https://github.com/HanCreation/Whisper-Tiny-German) |
|
|
| ## Model description |
|
|
| Model Parameter (pipe.model.num_parameters()): 37760640 (37M) |
| |
| ### 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: 8000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.2054 | 0.08 | 1000 | 0.7062 | 39.0698 | |
| | 0.1861 | 0.16 | 2000 | 0.6687 | 36.4857 | |
| | 0.1677 | 0.24 | 3000 | 0.6393 | 35.6849 | |
| | 0.2019 | 0.32 | 4000 | 0.6193 | 34.4385 | |
| | 0.1808 | 0.4 | 5000 | 0.6103 | 33.8459 | |
| | 0.1697 | 0.48 | 6000 | 0.5956 | 32.8519 | |
| | 0.1468 | 0.56 | 7000 | 0.5884 | 32.7029 | |
| | 0.1906 | 0.64 | 8000 | 0.5818 | 32.3327 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.40.2 |
| - Pytorch 2.3.0 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
