File size: 1,744 Bytes
395e803 7b1c102 395e803 7b1c102 963d3a3 7b1c102 4e69131 395e803 7b1c102 6e26360 7b1c102 511a339 7b1c102 74e5b4e 4e69131 7b1c102 1302198 7b1c102 74e5b4e 7b1c102 74e5b4e 7b1c102 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
language:
- no
license: apache-2.0
tags:
- whisper-event
- norwegian
datasets:
- NbAiLab/NCC_S
- NbAiLab/NPSC
- NbAiLab/NST
metrics:
- wer
model-index:
- name: Whisper Large 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: 10.718635559082031
---
# Whisper Large Norwegian Bokmål
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) 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: 0.2477
- Wer: 10.718635559082031
## 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: 64
- 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 warmpu
- lr_scheduler_warmup_steps: 1000
- training_steps: 50.000 (currently @1.000)
- mixed_precision_training: fp16
- deepspeed: true
### Live Training results
See [Tensorboad Metrics](https://huggingface.co/NbAiLab/whisper-large-v2-nob/tensorboard)
|