---
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-seed2025
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 20.039338734604037
      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-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: 0.4638
- Wer: 20.0393

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2511        | 0.3   | 39   | 0.9054          | 41.8161 |
| 0.6972        | 0.6   | 78   | 0.5555          | 23.7203 |
| 0.5503        | 0.9   | 117  | 0.5132          | 23.7765 |
| 0.4966        | 1.2   | 156  | 0.4943          | 21.6504 |
| 0.4841        | 1.5   | 195  | 0.4807          | 20.8027 |
| 0.4759        | 1.8   | 234  | 0.4732          | 20.3625 |
| 0.4804        | 2.1   | 273  | 0.4682          | 20.3531 |
| 0.4416        | 2.4   | 312  | 0.4672          | 21.1071 |
| 0.4385        | 2.7   | 351  | 0.4652          | 20.1798 |
| 0.4327        | 3.0   | 390  | 0.4638          | 20.0393 |


### Framework versions

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