Historical Swedish Bert Model
** WORK IN PROGRESS ** (Will be updated with bigger datasets soon + new OCR is coming to extend the dataset even further)
A historical Swedish Bert model is released from the National Swedish Archives to better generalise to Swedish historical text. Researches are well-aware that the Swedish language has been subject to change over time which means that present-day point-of-view models less ideal candidates for the job. However, this model can be used to interpret and analyse historical textual material and be fine-tuned for different downstream tasks.
Intended uses & limitations
This model should primarly be used to fine-tune further on and downstream tasks.
Inference for fill-mask with Huggingface Transformers in python:
from transformers import pipeline
summarizer = pipeline("fill-mask", model="Riksarkivet/bert-base-cased-swe-historical")
historical_text = """Det vore [MASK] häller nödvändigt att bita af tungan än berättat hvad jag varit med om."""
print(summarizer(historical_text))
Model Description
The training procedure can be recreated from here: Src_code. The preprocessing procedure can be recreated from here: Src_code.
Model: The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- fp16: False
Dataset (WIP):
- Khubist2, which has been cleaned and chunked. (will be further extended)
Acknowledgements
We gratefully acknowledge EuroHPC for funding this research by providing computing resources of the HPC system Vega and SWE-clarin for the datasets.
Citation Information
Eva Pettersson and Lars Borin (2022) Swedish Diachronic Corpus In Darja Fišer & Andreas Witt (eds.), CLARIN. The Infrastructure for Language Resources. Berlin: deGruyter. https://degruyter.com/document/doi/10.1515/9783110767377-022/html
