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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: exp4-whisper-all-jasmin
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 16.046566242828867
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. -->
# exp4-whisper-all-jasmin
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: 0.3347
- Wer: 16.0466
## 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: 48
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 150
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9942 | 0.2 | 100 | 1.1448 | 36.9041 |
| 0.7153 | 0.4 | 200 | 0.7109 | 33.2237 |
| 0.4752 | 0.6 | 300 | 0.4312 | 21.6157 |
| 0.4388 | 0.8 | 400 | 0.3911 | 20.1932 |
| 0.4234 | 1.0 | 500 | 0.3737 | 18.9419 |
| 0.417 | 1.2 | 600 | 0.3623 | 18.1199 |
| 0.4012 | 1.4 | 700 | 0.3544 | 17.8549 |
| 0.3898 | 1.6 | 800 | 0.3487 | 17.5127 |
| 0.4018 | 1.8 | 900 | 0.3445 | 17.3785 |
| 0.3736 | 2.0 | 1000 | 0.3415 | 15.7815 |
| 0.3804 | 2.2 | 1100 | 0.3389 | 16.2277 |
| 0.397 | 2.4 | 1200 | 0.3369 | 16.1338 |
| 0.3772 | 2.6 | 1300 | 0.3356 | 16.0935 |
| 0.3781 | 2.8 | 1400 | 0.3350 | 16.5968 |
| 0.3675 | 3.0 | 1500 | 0.3347 | 16.0466 |
### Framework versions
- PEFT 0.16.0
- Transformers 4.52.0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2 |