---
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