---
base_model: openai/whisper-base
datasets:
- mozilla-foundation/common_voice_17_0
language:
- nl
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Base NL
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: nl
      split: test
      args: 'config: nl, split: test'
    metrics:
    - type: wer
      value: 19.0031
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base NL

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.343928
- Wer: 19.003155

## 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: 1e-05
- train_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 7500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Step | Validation Loss | Wer     |
|:-------------:|:----:|:---------------:|:-------:|
| 0.3639        |  500 | 0.396971        | 24.3028 |
| 0.2625        | 1000 | 0.358340        | 22.5210 |
| 0.2212        | 1500 | 0.341232        | 21.0322 |
| 0.1455        | 2000 | 0.330033        | 20.2046 |
| 0.1406        | 2500 | 0.324484        | 20.0508 |
| 0.1244        | 3000 | 0.321562        | 19.5279 |
| 0.0848        | 3500 | 0.321506        | 19.5114 |
| 0.0844        | 4000 | 0.316492        | 19.1462 |
| 0.0731        | 4500 | 0.321992        | 19.0167 |
| 0.0515        | 5000 | 0.324720        | 19.1492 |
| 0.0532        | 5500 | 0.324773        | 19.0148 |
| 0.0426        | 6000 | 0.332404        | 19.0576 |
| 0.0328        | 6500 | 0.334900        | 18.8249 |
| 0.0327        | 7000 | 0.335876        | 19.0080 |
| 0.0252        | 7500 | 0.343928        | 19.0031 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1