---
language:
- sv
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 Sv
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: sv
      split: test[:10%]
      args: 'config: sv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 19.76284584980237
---

# Whisper Small Swedish
This model is an adapted version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset in Swedish.
It achieves the following results on the evaluation set:
- Wer: 19.8166

## Model description & uses

This model is the openai whisper small transformer adapted for Swedish audio to text transcription.
The model is available through its [HuggingFace web app](https://huggingface.co/spaces/torileatherman/whisper_small_sv)

## Training and evaluation data

Data used for training is the initial 10% of train and validation of [Swedish Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/sv/train) 11.0 from Mozilla Foundation.
The dataset used for evaluation is the initial 10% of test of Swedish Common Voice.
The training data has been augmented with random noise, random pitching and change of the speed of the voice.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- weight decay: 0

### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1379        | 0.95  | 1000 | 0.295811        | 21.467|
| 0.0245        | 2.86  | 3000 | 0.300059        | 20.160 |
| 0.0060        | 3.82  | 4000 | 0.320301        | 19.762 |

### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2