Instructions to use greenw0lf/whisper-new-nnat-5h-mmr-ecapa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use greenw0lf/whisper-new-nnat-5h-mmr-ecapa with PEFT:
Task type is invalid.
- Transformers
How to use greenw0lf/whisper-new-nnat-5h-mmr-ecapa with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("greenw0lf/whisper-new-nnat-5h-mmr-ecapa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| 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-5h-mmr-ecapa | |
| results: | |
| - task: | |
| type: automatic-speech-recognition | |
| name: Automatic Speech Recognition | |
| dataset: | |
| name: JASMIN-CGN | |
| type: jasmin | |
| metrics: | |
| - type: wer | |
| value: 35.10513745141198 | |
| 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-5h-mmr-ecapa | |
| 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: 0.5545 | |
| - Wer: 35.1051 | |
| ## 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: 62 | |
| - num_epochs: 3.0 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Wer | | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| | |
| | 0.9171 | 0.2967 | 62 | 0.7342 | 44.3497 | | |
| | 0.377 | 0.5933 | 124 | 0.6011 | 41.0902 | | |
| | 0.3449 | 0.8900 | 186 | 0.5843 | 42.5420 | | |
| | 0.315 | 1.1866 | 248 | 0.5710 | 39.1186 | | |
| | 0.2988 | 1.4833 | 310 | 0.5689 | 45.5393 | | |
| | 0.2893 | 1.7799 | 372 | 0.5588 | 37.1330 | | |
| | 0.2607 | 2.0766 | 434 | 0.5569 | 36.0230 | | |
| | 0.2532 | 2.3732 | 496 | 0.5575 | 35.7046 | | |
| | 0.2599 | 2.6699 | 558 | 0.5543 | 34.4776 | | |
| | 0.2716 | 2.9665 | 620 | 0.5545 | 35.1051 | | |
| ### Framework versions | |
| - PEFT 0.17.1 | |
| - Transformers 4.57.6 | |
| - Pytorch 2.8.0+cu128 | |
| - Datasets 4.5.0 | |
| - Tokenizers 0.22.2 |