Downloads · 30 days
8
36% of all-time downloads
arg_mining_us2016_propositions
Godfrey2712/arg_mining_us2016_propositions
arg_mining_us2016_propositions is a text classification model from Godfrey2712. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as ms-pl.
Classifies Coherent Propositional Contents of locution Pairs as either RA (Support), CA (Attack), or N/A Argument Relationship. N/A consists of instances where there are other and no argument relationships present in…
All-time downloads
22
Public
Parameters
435M
1.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.7 GB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- ms-pl
- Model type
- deberta-v2
- Access
- Public
- Created
- Jul 8, 2024
- Updated
- Mar 30, 2026
- SHA
- d9a799dc
Try a prompt
Model card
From the Hugging Face model README
Classifies Coherent Propositional Contents of locution Pairs as either RA (Support), CA (Attack), or N/A Argument Relationship. N/A consists of instances where there are other and no argument relationships present in the propositional content pairs.
Takes two coherent propositions and classifies as either Support, Attack, or N/A.
Results:
| precision | recall | f1-score | support | |
|---|---|---|---|---|
| CA | 0.59 | 0.52 | 0.55 | 149 |
| N/A | 0.72 | 0.73 | 0.72 | 688 |
| RA | 0.73 | 0.74 | 0.73 | 654 |
| accuracy | 0.71 | 1491 | ||
| macro avg | 0.68 | 0.66 | 0.67 | 1491 |
| weighted avg | 0.71 | 0.71 | 0.71 | 1491 |
Dataset: https://corpora.aifdb.org/US2016 The data preprocessing and fine-tuning technique can be found here: https://discovery.dundee.ac.uk/en/studentTheses/exploiting-illocutionary-forces-in-dialogue-structures-for-enhanc/
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- ms-pl
- Created
- Jul 8, 2024
- Updated
- Mar 30, 2026