---
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-maxcos-ecapa
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 26.431883107760036
      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-maxcos-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: 0.5305
- Wer: 26.4319

## 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: 91
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6936        | 0.2984 | 91   | 0.6340          | 45.6095 |
| 0.3958        | 0.5967 | 182  | 0.5687          | 33.3396 |
| 0.3687        | 0.8951 | 273  | 0.5474          | 28.3426 |
| 0.3232        | 1.1934 | 364  | 0.5466          | 29.8319 |
| 0.2992        | 1.4918 | 455  | 0.5458          | 27.5371 |
| 0.3277        | 1.7902 | 546  | 0.5312          | 26.2352 |
| 0.3002        | 2.0885 | 637  | 0.5286          | 25.6357 |
| 0.2726        | 2.3869 | 728  | 0.5317          | 27.2655 |
| 0.2821        | 2.6852 | 819  | 0.5328          | 26.3991 |
| 0.2643        | 2.9836 | 910  | 0.5305          | 26.4319 |


### Framework versions

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