| --- |
| library_name: peft |
| language: |
| - nl |
| license: apache-2.0 |
| base_model: openai/whisper-large-v2 |
| tags: |
| - base_model:adapter:openai/whisper-large-v2 |
| - lora |
| - transformers |
| datasets: |
| - jasmin |
| - jasmin-cgn |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-new-nnat-20h-meta-seed2025 |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: JASMIN-CGN |
| type: jasmin |
| metrics: |
| - type: wer |
| value: 20.039338734604037 |
| 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. --> |
|
|
| # whisper-new-nnat-20h-meta-seed2025 |
|
|
| This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the JASMIN-CGN dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4638 |
| - Wer: 20.0393 |
|
|
| ## 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: 48 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 39 |
| - num_epochs: 3.0 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 1.2511 | 0.3 | 39 | 0.9054 | 41.8161 | |
| | 0.6972 | 0.6 | 78 | 0.5555 | 23.7203 | |
| | 0.5503 | 0.9 | 117 | 0.5132 | 23.7765 | |
| | 0.4966 | 1.2 | 156 | 0.4943 | 21.6504 | |
| | 0.4841 | 1.5 | 195 | 0.4807 | 20.8027 | |
| | 0.4759 | 1.8 | 234 | 0.4732 | 20.3625 | |
| | 0.4804 | 2.1 | 273 | 0.4682 | 20.3531 | |
| | 0.4416 | 2.4 | 312 | 0.4672 | 21.1071 | |
| | 0.4385 | 2.7 | 351 | 0.4652 | 20.1798 | |
| | 0.4327 | 3.0 | 390 | 0.4638 | 20.0393 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.17.1 |
| - Transformers 4.57.6 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
