| --- |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - facebook/voxpopuli |
| metrics: |
| - wer |
| model-index: |
| - name: WhisperForSpokenNER-end2end |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: facebook/voxpopuli de+es+fr+nl |
| type: facebook/voxpopuli |
| config: de+es+fr+nl |
| split: None |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.14642407057340895 |
| --- |
| |
| <!-- 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. --> |
|
|
| # WhisperForSpokenNER-end2end |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/voxpopuli de+es+fr+nl dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3933 |
| - Wer: 0.1464 |
|
|
| ## 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 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 5000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.3562 | 0.36 | 200 | 0.3265 | 0.1920 | |
| | 0.3149 | 0.71 | 400 | 0.3136 | 0.1842 | |
| | 0.2778 | 1.07 | 600 | 0.3204 | 0.1786 | |
| | 0.2288 | 1.43 | 800 | 0.3156 | 0.1717 | |
| | 0.2307 | 1.79 | 1000 | 0.3056 | 0.1708 | |
| | 0.1482 | 2.14 | 1200 | 0.3138 | 0.1682 | |
| | 0.1368 | 2.5 | 1400 | 0.3136 | 0.1656 | |
| | 0.1405 | 2.86 | 1600 | 0.3082 | 0.1617 | |
| | 0.0639 | 3.22 | 1800 | 0.3201 | 0.1612 | |
| | 0.0673 | 3.57 | 2000 | 0.3242 | 0.1612 | |
| | 0.0688 | 3.93 | 2200 | 0.3235 | 0.1584 | |
| | 0.0227 | 4.29 | 2400 | 0.3420 | 0.1558 | |
| | 0.0232 | 4.65 | 2600 | 0.3430 | 0.1525 | |
| | 0.0229 | 5.0 | 2800 | 0.3450 | 0.1528 | |
| | 0.0064 | 5.36 | 3000 | 0.3631 | 0.1498 | |
| | 0.0059 | 5.72 | 3200 | 0.3652 | 0.1482 | |
| | 0.0043 | 6.08 | 3400 | 0.3756 | 0.1482 | |
| | 0.0021 | 6.43 | 3600 | 0.3798 | 0.1477 | |
| | 0.002 | 6.79 | 3800 | 0.3824 | 0.1484 | |
| | 0.0014 | 7.15 | 4000 | 0.3876 | 0.1471 | |
| | 0.0013 | 7.51 | 4200 | 0.3900 | 0.1473 | |
| | 0.0013 | 7.86 | 4400 | 0.3917 | 0.1461 | |
| | 0.0012 | 8.22 | 4600 | 0.3929 | 0.1462 | |
| | 0.0012 | 8.58 | 4800 | 0.3932 | 0.1465 | |
| | 0.0012 | 8.94 | 5000 | 0.3933 | 0.1464 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.1.0 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
