|
--- |
|
language: nl |
|
license: mit |
|
datasets: |
|
- dbrd |
|
model-index: |
|
- name: robbert-v2-dutch-sentiment Copied |
|
results: |
|
- task: |
|
type: text-classification |
|
name: Text Classification |
|
dataset: |
|
name: dbrd |
|
type: sentiment-analysis |
|
split: test |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.93325 |
|
widget: |
|
- text: "Ik erken dat dit een boek is, daarmee is alles gezegd." |
|
- text: "Prachtig verhaal, heel mooi verteld en een verrassend einde... Een topper!" |
|
thumbnail: "https://github.com/iPieter/RobBERT/raw/master/res/robbert_logo.png" |
|
tags: |
|
- Dutch |
|
- Flemish |
|
- RoBERTa |
|
- RobBERT |
|
--- |
|
|
|
<p align="center"> |
|
<img src="https://github.com/iPieter/RobBERT/raw/master/res/robbert_logo_with_name.png" alt="RobBERT: A Dutch RoBERTa-based Language Model" width="75%"> |
|
</p> |
|
|
|
# RobBERT finetuned for sentiment analysis on DBRD |
|
|
|
This is a finetuned model based on [RobBERT (v2)](https://huggingface.co/pdelobelle/robbert-v2-dutch-base). We used [DBRD](https://huggingface.co/datasets/dbrd), which consists of book reviews from [hebban.nl](hebban.nl). Hence our example sentences about books. We did some limited experiments to test if this also works for other domains, but this was not |
|
|
|
# Training data and setup |
|
We used the [Dutch Book Reviews Dataset (DBRD)](https://huggingface.co/datasets/dbrd) from van der Burgh et al. (2019). |
|
Originally, these reviews got a five-star rating, but this has been converted to positive (⭐️⭐️⭐️⭐️ and ⭐️⭐️⭐️⭐️⭐️), neutral (⭐️⭐️⭐️) and negative (⭐️ and ⭐️⭐️). |
|
We used 19.5k reviews for the training set, 528 reviews for the validation set and 2224 to calculate the final accuracy. |
|
|
|
The validation set was used to evaluate a random hyperparameter search over the learning rate, weight decay and gradient accumulation steps. |
|
The full training details are available in [`training_args.bin`](https://huggingface.co/DTAI-KULeuven/robbert-v2-dutch-sentiment/blob/main/training_args.bin) as a binary PyTorch file. |
|
|
|
# Limitations and biases |
|
- The domain of the reviews is limited to book reviews. |
|
- Most authors of the book reviews were women, which could have caused [a difference in performance for reviews written by men and women](https://www.aclweb.org/anthology/2020.findings-emnlp.292). |
|
|
|
## Credits and citation |
|
|
|
This project is created by [Pieter Delobelle](https://people.cs.kuleuven.be/~pieter.delobelle), [Thomas Winters](https://thomaswinters.be) and [Bettina Berendt](https://people.cs.kuleuven.be/~bettina.berendt/). |
|
If you would like to cite our paper or models, you can use the following BibTeX: |
|
|
|
``` |
|
@inproceedings{delobelle2020robbert, |
|
title = "{R}ob{BERT}: a {D}utch {R}o{BERT}a-based {L}anguage {M}odel", |
|
author = "Delobelle, Pieter and |
|
Winters, Thomas and |
|
Berendt, Bettina", |
|
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020", |
|
month = nov, |
|
year = "2020", |
|
address = "Online", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://www.aclweb.org/anthology/2020.findings-emnlp.292", |
|
doi = "10.18653/v1/2020.findings-emnlp.292", |
|
pages = "3255--3265" |
|
} |
|
``` |
