metadata

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 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

Training and evaluation data

Data used for training is the initial 10% of train and validation of Swedish Common Voice 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