metadata

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

Whisper Tiny Nordic

This model is a fine-tuned version of 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