---
language:
- nn
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-npsc
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: 16K_mp3_bokmaal
      split: train
      args: 16K_mp3_bokmaal
    metrics:
    - name: Wer
      type: wer
      value: 12.925418803583286
---

<!-- 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-small-npsc

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2028
- Wer: 12.9254

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3922        | 0.18  | 500  | 0.3975          | 24.2055 |
| 0.2893        | 0.36  | 1000 | 0.3139          | 20.1507 |
| 0.2471        | 0.54  | 1500 | 0.2733          | 17.4449 |
| 0.2159        | 0.72  | 2000 | 0.2488          | 16.2681 |
| 0.2195        | 0.89  | 2500 | 0.2304          | 15.0577 |
| 0.1178        | 1.07  | 3000 | 0.2245          | 14.5968 |
| 0.1099        | 1.25  | 3500 | 0.2183          | 14.1118 |
| 0.1059        | 1.43  | 4000 | 0.2136          | 13.7914 |
| 0.1156        | 1.61  | 4500 | 0.2072          | 13.7491 |
| 0.1025        | 1.79  | 5000 | 0.2034          | 13.1515 |
| 0.1123        | 1.97  | 5500 | 0.2006          | 13.0284 |
| 0.0734        | 2.15  | 6000 | 0.2028          | 12.9254 |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1