---
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-caps-ecapa
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: JASMIN-CGN
      type: jasmin
    metrics:
    - type: wer
      value: 20.41399334988058
      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-caps-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: 0.4515
- Wer: 20.4140

## 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: 104
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5877        | 0.2989 | 104  | 0.5724          | 26.2118 |
| 0.3882        | 0.5977 | 208  | 0.5024          | 22.1608 |
| 0.3917        | 0.8966 | 312  | 0.4835          | 21.9548 |
| 0.3331        | 1.1954 | 416  | 0.4741          | 21.4818 |
| 0.3337        | 1.4943 | 520  | 0.4647          | 22.0812 |
| 0.3604        | 1.7931 | 624  | 0.4574          | 21.0088 |
| 0.3182        | 2.0920 | 728  | 0.4540          | 21.0134 |
| 0.3104        | 2.3908 | 832  | 0.4552          | 20.5685 |
| 0.2996        | 2.6897 | 936  | 0.4529          | 20.3718 |
| 0.2894        | 2.9885 | 1040 | 0.4515          | 20.4140 |


### Framework versions

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