Repository containing the experiments described in our paper for the GermEval 2021 challenge: "Identifying German toxic, engaging, and fact-claiming comments with ensemble learning (FHAC at GermEval 2021)" (available online).
The train and test data can be found in the folder dataset. Experiments and their results are filed in experiments. The folder figures contains the scripts that were used to create the figures in our paper.
| number | description | single- or multi-label |
|---|---|---|
| model exploration | ||
| 1 | 50 gelectra | multi-label |
| 2 | 50 gbert | multi-label |
| 3 | 25 gelectra + 25 gbert | multi-label |
| 4 | 25 gelectra + 25 gbert | single-label |
| submissions | ||
| 5 | submission 1, 200 gelectra | multi-label |
| 6 | submission 2, 200 gelectra + 200 gbert | multi-label |
| 7 | submission 3, 30 gelectra + 30 gbert | single-label |
The experiments were run in a conda environment with python 3.9. You can find most of the required packages and the command for creating a new environemnt in the requirements.txt. In addition to the packages described in the requirements.txt, two packages were installed using pip:
pip install emojipip install transformers