|
--- |
|
language: |
|
- no |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- norwegian |
|
datasets: |
|
- NbAiLab/NCC_S |
|
- NbAiLab/NPSC |
|
- NbAiLab/NST |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Tiny 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: 32.76 |
|
--- |
|
|
|
# Whisper Tiny Norwegian Bokmål |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) trained on several datasets. |
|
|
|
It is currently in the middle of a large training. Currently it achieves the following results on the evaluation set: |
|
- Loss: 0.604 |
|
- Wer: 32.76 |
|
|
|
## Model description |
|
|
|
The model is trained on a large corpus of roughly 5.000 hours of voice. The sources are subtitles from the Norwegian broadcaster NRK, transcribed speeches from the Norwegian parliament and voice recordings from Norsk Språkteknologi. |
|
|
|
## 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 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- training_steps: 100.000 (currently @5.000) |
|
- mixed_precision_training: fp16 |
|
|
|
### Live Training results |
|
See [Tensorboad Metrics](https://huggingface.co/NbAiLab/whisper-tiny-nob/tensorboard) |
|
|
|
|
|
|
|
|
