---
datasets:
- samirmsallem/argument_mining_de
language:
- de
metrics:
- accuracy
base_model:
- deepset/gbert-base
pipeline_tag: text-classification
library_name: transformers
model-index:
- name: checkpoints
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: samirmsallem/argument_mining_de
      type: samirmsallem/argument_mining_de
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9657534246575342
---

## Text classification model for argument mining and detection


**gbert-base-argument_mining** is a text classification model in the scientific domain in German, finetuned from the model [gbert-base](https://huggingface.co/deepset/gbert-base). 
It was trained using a [synthetically created, annotated dataset](https://huggingface.co/datasets/samirmsallem/argument_mining_de) containing different sentence types occuring in conclusions of scientific theses and papers.


### Training

Training was conducted on a 10 epoch fine-tuning approach, however this repository contains the results of the fourth epoch, since it has the best accuracy:

| epoch | accuracy          | loss               |
|-------|-------------------|--------------------|
| 1.0   | 0.9315            | 0.3872             |
| 2.0   | 0.9178            | 0.2987             |
| 3.0   | 0.9589            | 0.1519             |
| 4.0   | **0.9658**        | **0.1162**         |
| 5.0   | 0.9521            | 0.2100             |
| 6.0   | 0.9521            | 0.1979             |
| 7.0   | 0.9521            | 0.2453             |
| 8.0   | 0.9521            | 0.2251             |
| 9.0   | 0.9452            | 0.2225             |
| 10.0  | 0.9521            | 0.2286             |

        

In relation to the dataset, the model demonstrates that it can effectively learn to distinguish between the two classes claim and premise. However, the rapid onset of overfitting after epoch 4 suggests that the dataset is imbalanced and noisy. Further work should enable the model to be trained on more robust data to ensure better evaluation results.

### Text Classification Tags

|Text Classification Tag| Text Classification Label | 
| :----:                |    :----:                 | 
| 0                     | CLAIM          |
| 1                     | COUNTERCLAIM          |
| 2                     | LINK          |
| 3                     | CONC          |
| 4                     | FUT          |
| 5                     | OTH          |