---
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-meta-seed333
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 19.997190090385423
      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-meta-seed333

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: 0.4644
- Wer: 19.9972

## 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: 39
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2682        | 0.3   | 39   | 0.9069          | 45.0616 |
| 0.6645        | 0.6   | 78   | 0.5525          | 24.3245 |
| 0.5616        | 0.9   | 117  | 0.5117          | 22.0344 |
| 0.5156        | 1.2   | 156  | 0.4948          | 21.1867 |
| 0.4889        | 1.5   | 195  | 0.4835          | 21.0228 |
| 0.4997        | 1.8   | 234  | 0.4739          | 20.5732 |
| 0.4574        | 2.1   | 273  | 0.4687          | 20.3718 |
| 0.4434        | 2.4   | 312  | 0.4669          | 20.6013 |
| 0.4495        | 2.7   | 351  | 0.4651          | 20.7886 |
| 0.4197        | 3.0   | 390  | 0.4644          | 19.9972 |


### Framework versions

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