---
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-caps-ecapa
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 23.963845829625814
      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-caps-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: 0.5138
- Wer: 23.9638

## 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: 32
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.2318        | 0.2991 | 32   | 0.9904          | 46.0029 |
| 0.5262        | 0.5981 | 64   | 0.6141          | 29.3120 |
| 0.4205        | 0.8972 | 96   | 0.5630          | 26.0151 |
| 0.4261        | 1.1963 | 128  | 0.5430          | 24.1886 |
| 0.3874        | 1.4953 | 160  | 0.5303          | 23.8702 |
| 0.3709        | 1.7944 | 192  | 0.5222          | 25.4063 |
| 0.3507        | 2.0935 | 224  | 0.5185          | 25.0925 |
| 0.3254        | 2.3925 | 256  | 0.5164          | 24.5727 |
| 0.3059        | 2.6916 | 288  | 0.5143          | 23.5283 |
| 0.3325        | 2.9907 | 320  | 0.5138          | 23.9638 |


### Framework versions

- PEFT 0.17.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2