---
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-10h-caps-ecapa
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 21.692502224511777
      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-10h-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: 0.4781
- Wer: 21.6925

## 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: 59
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.4332        | 0.2995 | 59   | 0.6828          | 31.1806 |
| 0.4937        | 0.5990 | 118  | 0.5383          | 23.9873 |
| 0.3968        | 0.8985 | 177  | 0.5136          | 23.0366 |
| 0.402         | 1.1980 | 236  | 0.5016          | 22.7369 |
| 0.3518        | 1.4975 | 295  | 0.4921          | 21.8517 |
| 0.3556        | 1.7970 | 354  | 0.4859          | 22.0344 |
| 0.3345        | 2.0964 | 413  | 0.4839          | 21.9313 |
| 0.3128        | 2.3959 | 472  | 0.4810          | 21.9220 |
| 0.3074        | 2.6954 | 531  | 0.4791          | 21.7253 |
| 0.3198        | 2.9949 | 590  | 0.4781          | 21.6925 |


### Framework versions

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