| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: openai/whisper-small |
| datasets: |
| - facebook/voxpopuli |
| metrics: |
| - wer |
| model-index: |
| - name: WhisperForSpokenNER-end2end |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: facebook/voxpopuli de+es+fr+nl |
| type: facebook/voxpopuli |
| split: None |
| metrics: |
| - type: wer |
| value: 0.1421388512860182 |
| name: Wer |
| --- |
| |
| <!-- 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: 0.3440 |
| - Combined Wer: 0.2231 |
| - F1 Score: 0.5368 |
| - Label F1: 0.6908 |
| - Wer: 0.1421 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - 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 | Combined Wer | F1 Score | Label F1 | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------------:|:--------:|:--------:|:------:| |
| | 1.1583 | 0.1 | 500 | 1.0361 | 0.3217 | 0.0746 | 0.1415 | 0.2067 | |
| | 0.4069 | 0.2 | 1000 | 0.4111 | 0.2203 | 0.4223 | 0.5940 | 0.1235 | |
| | 0.3708 | 0.3 | 1500 | 0.3768 | 0.2201 | 0.4609 | 0.6267 | 0.1295 | |
| | 0.3512 | 0.4 | 2000 | 0.3624 | 0.2223 | 0.5142 | 0.6835 | 0.1359 | |
| | 0.3411 | 0.5 | 2500 | 0.3543 | 0.2204 | 0.5225 | 0.6883 | 0.1374 | |
| | 0.3313 | 1.02 | 3000 | 0.3492 | 0.2235 | 0.5193 | 0.6808 | 0.1398 | |
| | 0.3252 | 1.12 | 3500 | 0.3459 | 0.2251 | 0.5333 | 0.6893 | 0.1436 | |
| | 0.3293 | 1.22 | 4000 | 0.3447 | 0.2237 | 0.5325 | 0.6860 | 0.1416 | |
| | 0.321 | 1.32 | 4500 | 0.3443 | 0.2238 | 0.5366 | 0.6905 | 0.1425 | |
| | 0.3223 | 1.42 | 5000 | 0.3440 | 0.2231 | 0.5368 | 0.6908 | 0.1421 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.7.1.dev0 |
| - Transformers 4.37.0.dev0 |
| - Pytorch 2.1.0 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
