---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
language:
- 'no'
- nb
datasets:
- NbAiLab/NCC_S
metrics:
- wer
model-index:
- name: Whisper Large Norwegian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: NbAiLab/NCC_S
      type: NbAiLab/NCC_S
      config: 'no'
      split: validation
      args: 'no'
    metrics:
    - name: Wer
      type: wer
      value: 12.51522533495737
---

<!-- 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 Large Norwegian

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the NbAiLab/NCC_S dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2776
- Wer: 12.5152

## 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: 12
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6892        | 0.2   | 1000 | 0.3177          | 15.1035 |
| 0.6782        | 0.4   | 2000 | 0.3033          | 13.4592 |
| 0.6317        | 0.6   | 3000 | 0.2909          | 13.7637 |
| 0.5609        | 0.8   | 4000 | 0.2803          | 12.6675 |
| 0.5726        | 1.0   | 5000 | 0.2776          | 12.5152 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.11.0