--- language: - danish - norwegian - swedish 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 dataset: name: mozilla-foundation/common_voice_11_0 nn-NO type: mozilla-foundation/common_voice_11_0 config: null split: None metrics: - name: Wer type: wer value: 87.65957446808511 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: babelbox/babelbox_voice nst type: babelbox/babelbox_voice metrics: - name: Wer type: wer value: 87.65957446808511 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: NbAiLab/NST no-distant type: NbAiLab/NST metrics: - name: Wer type: wer value: 87.65957446808511 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: NbAiLab/NPSC 16K_mp3_nynorsk type: NbAiLab/NPSC metrics: - name: Wer type: wer value: 87.65957446808511 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: google/fleurs nb_no type: google/fleurs metrics: - name: Wer type: wer value: 87.65957446808511 --- # 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, the mozilla-foundation/common_voice_11_0 da, the mozilla-foundation/common_voice_11_0 nn-NO, the babelbox/babelbox_voice nst, the NbAiLab/NST no-distant, the NbAiLab/NPSC 16K_mp3_nynorsk, the google/fleurs sv_se, the google/fleurs da_dk and the google/fleurs nb_no datasets. 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