---
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-maxcos-ecapa
  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-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: 0.4646
- 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: 109
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.322         | 0.2986 | 109  | 0.5722          | 26.5302 |
| 0.421         | 0.5973 | 218  | 0.5081          | 23.2661 |
| 0.3857        | 0.8959 | 327  | 0.4898          | 21.8892 |
| 0.3523        | 1.1945 | 436  | 0.4843          | 21.9360 |
| 0.3301        | 1.4932 | 545  | 0.4772          | 21.4864 |
| 0.3187        | 1.7918 | 654  | 0.4686          | 21.2336 |
| 0.328         | 2.0904 | 763  | 0.4704          | 20.9713 |
| 0.2973        | 2.3890 | 872  | 0.4684          | 20.6201 |
| 0.2979        | 2.6877 | 981  | 0.4659          | 20.5264 |
| 0.2836        | 2.9863 | 1090 | 0.4646          | 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