| --- |
| 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: 0.059877955758962625 |
| --- |
| |
| <!-- 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: 0.4253 |
| - F1 Score: 0.7984 |
| - Label F1: 0.8971 |
| - Wer: 0.0599 |
|
|
| ## 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: 64 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:| |
| | 0.4435 | 0.36 | 200 | 0.4357 | 0.4513 | 0.7168 | 0.0599 | |
| | 0.4309 | 0.71 | 400 | 0.4306 | 0.6751 | 0.8354 | 0.0599 | |
| | 0.4235 | 1.07 | 600 | 0.4282 | 0.6722 | 0.8548 | 0.0599 | |
| | 0.4267 | 1.43 | 800 | 0.4269 | 0.7073 | 0.8455 | 0.0599 | |
| | 0.4254 | 1.79 | 1000 | 0.4264 | 0.7273 | 0.8678 | 0.0599 | |
| | 0.4264 | 2.14 | 1200 | 0.4264 | 0.7398 | 0.8780 | 0.0599 | |
| | 0.4206 | 2.5 | 1400 | 0.4262 | 0.7206 | 0.8583 | 0.0599 | |
| | 0.4232 | 2.86 | 1600 | 0.4260 | 0.7410 | 0.8685 | 0.0599 | |
| | 0.4249 | 3.22 | 1800 | 0.4255 | 0.7603 | 0.8926 | 0.0599 | |
| | 0.4239 | 3.57 | 2000 | 0.4256 | 0.7631 | 0.8835 | 0.0599 | |
| | 0.4213 | 3.93 | 2200 | 0.4255 | 0.7692 | 0.8988 | 0.0599 | |
| | 0.4213 | 4.29 | 2400 | 0.4256 | 0.7769 | 0.8926 | 0.0599 | |
| | 0.4244 | 4.65 | 2600 | 0.4253 | 0.7711 | 0.8996 | 0.0599 | |
| | 0.4234 | 5.0 | 2800 | 0.4254 | 0.7386 | 0.8797 | 0.0599 | |
| | 0.4222 | 5.36 | 3000 | 0.4252 | 0.7917 | 0.9 | 0.0599 | |
| | 0.4239 | 5.72 | 3200 | 0.4254 | 0.7801 | 0.8963 | 0.0599 | |
| | 0.4201 | 6.08 | 3400 | 0.4254 | 0.7950 | 0.8954 | 0.0599 | |
| | 0.4194 | 6.43 | 3600 | 0.4253 | 0.7851 | 0.9008 | 0.0599 | |
| | 0.4203 | 6.79 | 3800 | 0.4252 | 0.7934 | 0.9091 | 0.0599 | |
| | 0.4214 | 7.15 | 4000 | 0.4253 | 0.8050 | 0.9046 | 0.0599 | |
| | 0.4206 | 7.51 | 4200 | 0.4253 | 0.8 | 0.9 | 0.0599 | |
| | 0.4205 | 7.86 | 4400 | 0.4253 | 0.8050 | 0.9129 | 0.0599 | |
| | 0.4207 | 8.22 | 4600 | 0.4253 | 0.7951 | 0.9016 | 0.0599 | |
| | 0.4218 | 8.58 | 4800 | 0.4253 | 0.7984 | 0.8971 | 0.0599 | |
| | 0.4201 | 8.94 | 5000 | 0.4253 | 0.7984 | 0.8971 | 0.0599 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.1.0 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
