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---
language:
- 'no'
- sv
- da
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- mozilla-foundation/common_voice_11_0
- mozilla-foundation/common_voice_11_0
- babelbox/babelbox_voice
- NbAiLab/NST
- NbAiLab/NPSC
- google/fleurs
- google/fleurs
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Tiny Nordic
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    metrics:
    - name: Wer
      type: wer
      value: 87.65957446808511
---

<!-- 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 Tiny Nordic

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 sv-SE
mozilla-foundation/common_voice_11_0 da
mozilla-foundation/common_voice_11_0 nn-NO
babelbox/babelbox_voice nst
NbAiLab/NST no-distant
NbAiLab/NPSC 16K_mp3_nynorsk
google/fleurs sv_se
google/fleurs da_dk
google/fleurs nb_no dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1226
- Wer: 87.6596

## 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: 1
- eval_batch_size: 1
- 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: 1
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2