---
library_name: transformers
tags:
- argumentation
license: apache-2.0
datasets:
- Kleo/ArgKP_2021_GR
language:
- el
metrics:
- precision
base_model:
- ilsp/Meltemi-7B-v1
pipeline_tag: text-classification
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
This is a Meltemi-7b-v1 adapter model for a sequence classification task. 
It classifies keypoint-argument pairs as Matching/Non-matching. It was developed in the process of the KeyPoint Matching subtask of the [Key Point Analysis|Quantitative Argument Summarization Shared Task](https://github.com/IBM/KPA_2021_shared_task) as a solution for a low-resource language, Greek. 
The classifier was trained on the official shared task's dataset (ArgKP-2021) in a machine translated version for Greek with madlad-400-3b. For details refer to ArgKP-2021-GR dataset. 


## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** https://huggingface.co/Kleo
- **Shared by [optional]:** https://huggingface.co/Kleo
- **Model type:** adapter
- **Language(s) (NLP):** el/GR
- **License:** Apache license 2.0
- **Finetuned from model [optional]:**  [ilsp/Meltemi-7B-v1](https://huggingface.co/ilsp/Meltemi-7B-v1)

### Model Sources [optional]

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- **Repository:**  https://github.com/Kleo-Karap/KPA_thesis
- **Paper [optional]:** [More Information Needed]

## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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[More Information Needed]

### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

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[ArgKP_2021_GR]](https://huggingface.co/datasets/Kleo/ArgKP_2021_GR)

### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

```
@masterthesis{3456844,
    title = "Key Point Analysis in Greek: A New Dataset and Baselines",
    authorField = "Καραπαναγιώτου, Κλεοπάτρα",
    year = "2025",
    school = "ΠΜΣ Γλωσσική Τεχνολογία, Εθνικό και Καποδιστριακό Πανεπιστήμιο Αθηνών"
}
```

**APA:**

Karapanagiotou, K. (2025). Key Point Analysis in Greek: A New Dataset and Baselines [MSc Thesis, National and Kapodistrian University of Athens]. Pergamos.https://pergamos.lib.uoa.gr/uoa/dl/frontend/el/browse/3456844


## Model Card Contact

https://huggingface.co/Kleo