| --- |
| language: |
| - da |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - mozilla-foundation/common_voice_13_0 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Base Danish - WasuratS |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 13 |
| type: mozilla-foundation/common_voice_13_0 |
| config: da |
| split: test |
| args: da |
| metrics: |
| - name: Wer |
| type: wer |
| value: 39.73630725936735 |
| --- |
| |
| <!-- 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 Base Danish - WasuratS |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 13 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9795 |
| - Wer Ortho: 45.5986 |
| - Wer: 39.7363 |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 6000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
| | 0.5156 | 1.61 | 500 | 0.7387 | 47.8293 | 42.2586 | |
| | 0.2086 | 3.22 | 1000 | 0.7157 | 46.7087 | 41.0652 | |
| | 0.1439 | 4.82 | 1500 | 0.7300 | 46.5367 | 40.9610 | |
| | 0.0514 | 6.43 | 2000 | 0.7804 | 45.2963 | 39.5279 | |
| | 0.027 | 8.04 | 2500 | 0.8314 | 46.3126 | 40.3825 | |
| | 0.0133 | 9.65 | 3000 | 0.8739 | 44.8585 | 39.2777 | |
| | 0.0053 | 11.25 | 3500 | 0.9081 | 45.4839 | 39.7103 | |
| | 0.0041 | 12.86 | 4000 | 0.9347 | 45.4110 | 39.7050 | |
| | 0.0028 | 14.47 | 4500 | 0.9535 | 46.0624 | 40.3096 | |
| | 0.0024 | 16.08 | 5000 | 0.9673 | 45.6351 | 39.8979 | |
| | 0.0021 | 17.68 | 5500 | 0.9762 | 45.7862 | 39.9187 | |
| | 0.002 | 19.29 | 6000 | 0.9795 | 45.5986 | 39.7363 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.29.2 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
