| --- |
| license: apache-2.0 |
| base_model: openai/whisper-large-v2 |
| tags: |
| - whisper-event |
| - generated_from_trainer |
| datasets: |
| - facebook/voxpopuli |
| metrics: |
| - wer |
| model-index: |
| - name: WhisperForSpokenNER |
| 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: 0.06196300023221612 |
| --- |
| |
| <!-- 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 |
|
|
| This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the facebook/voxpopuli de+es+fr+nl dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2797 |
| - F1 Score: 0.7918 |
| - Label F1: 0.8933 |
| - Wer: 0.0620 |
|
|
| ## 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: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 32 |
| - 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 | F1 Score | Label F1 | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:| |
| | 0.1748 | 0.36 | 200 | 0.1706 | 0.6541 | 0.8032 | 0.0656 | |
| | 0.1754 | 0.71 | 400 | 0.1769 | 0.7194 | 0.8502 | 0.0674 | |
| | 0.1606 | 1.07 | 600 | 0.1856 | 0.6991 | 0.8407 | 0.0708 | |
| | 0.1282 | 1.43 | 800 | 0.1835 | 0.7455 | 0.8724 | 0.0728 | |
| | 0.131 | 1.79 | 1000 | 0.1762 | 0.7331 | 0.8691 | 0.0713 | |
| | 0.0804 | 2.14 | 1200 | 0.1792 | 0.7544 | 0.8744 | 0.0685 | |
| | 0.0712 | 2.5 | 1400 | 0.1833 | 0.75 | 0.8846 | 0.0691 | |
| | 0.0746 | 2.86 | 1600 | 0.1800 | 0.7554 | 0.8732 | 0.0738 | |
| | 0.0331 | 3.22 | 1800 | 0.1992 | 0.7757 | 0.8804 | 0.0702 | |
| | 0.0363 | 3.57 | 2000 | 0.1938 | 0.7625 | 0.8805 | 0.0688 | |
| | 0.037 | 3.93 | 2200 | 0.1986 | 0.7771 | 0.8865 | 0.0677 | |
| | 0.0153 | 4.29 | 2400 | 0.2125 | 0.7765 | 0.8794 | 0.0666 | |
| | 0.0144 | 4.65 | 2600 | 0.2115 | 0.7763 | 0.8922 | 0.0681 | |
| | 0.0148 | 5.0 | 2800 | 0.2180 | 0.7781 | 0.8891 | 0.0647 | |
| | 0.0058 | 5.36 | 3000 | 0.2310 | 0.7918 | 0.8913 | 0.0629 | |
| | 0.0058 | 5.72 | 3200 | 0.2268 | 0.7828 | 0.8938 | 0.0627 | |
| | 0.0036 | 6.08 | 3400 | 0.2462 | 0.7911 | 0.8937 | 0.0621 | |
| | 0.0019 | 6.43 | 3600 | 0.2493 | 0.7948 | 0.8950 | 0.0629 | |
| | 0.0016 | 6.79 | 3800 | 0.2543 | 0.7917 | 0.8980 | 0.0631 | |
| | 0.0009 | 7.15 | 4000 | 0.2667 | 0.7880 | 0.8944 | 0.0619 | |
| | 0.0007 | 7.51 | 4200 | 0.2735 | 0.7909 | 0.8934 | 0.0624 | |
| | 0.0007 | 7.86 | 4400 | 0.2756 | 0.7901 | 0.8926 | 0.0621 | |
| | 0.0005 | 8.22 | 4600 | 0.2779 | 0.7913 | 0.8931 | 0.0624 | |
| | 0.0004 | 8.58 | 4800 | 0.2795 | 0.7909 | 0.8932 | 0.0620 | |
| | 0.0005 | 8.94 | 5000 | 0.2797 | 0.7918 | 0.8933 | 0.0620 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.1.0 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
