---
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-20h-random-seed2025
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 20.694984311337986
      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-20h-random-seed2025

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: 0.4691
- Wer: 20.6950

## 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: 45
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8351        | 0.3   | 45   | 0.8048          | 39.6806 |
| 0.4512        | 0.6   | 90   | 0.5502          | 24.4649 |
| 0.4241        | 0.9   | 135  | 0.5124          | 23.5611 |
| 0.3697        | 1.2   | 180  | 0.4979          | 22.1374 |
| 0.3582        | 1.5   | 225  | 0.4848          | 21.3928 |
| 0.363         | 1.8   | 270  | 0.4774          | 21.5942 |
| 0.3568        | 2.1   | 315  | 0.4744          | 20.7886 |
| 0.3357        | 2.4   | 360  | 0.4710          | 20.6669 |
| 0.3389        | 2.7   | 405  | 0.4697          | 20.8402 |
| 0.338         | 3.0   | 450  | 0.4691          | 20.6950 |


### Framework versions

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