metadata
language:
- 'no'
license: apache-2.0
tags:
- whisper-event
- norwegian
datasets:
- NbAiLab/NCC_S
- NbAiLab/NPSC
- NbAiLab/NST
metrics:
- wer
model-index:
- name: Whisper Small Norwegian Bokmål
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: FLEURS
type: google/fleurs
config: nb_no
split: validation
args: nb_no
metrics:
- name: Wer
type: wer
value: 15.56
Whisper Small Norwegian Bokmål
This model is a fine-tuned version of openai/whisper-small trained on NCC_S_3-NRKonly.
It is currently in the middle of a large training.
Model description
The model is trained on a large corpus of roughly 4.000 hours of voice. The sources are subtitles from the Norwegian broadcaster NRK.
Intended uses & limitations
The model will be free for everyone to use when it is finished.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 128
- gradient_accumulation_steps: 2
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant with warmup
- lr_scheduler_warmup_steps: 1000
- training_steps: 50.000 (currently @1.000)
- mixed_precision_training: fp16
- deepspeed: true