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---
language: en
pipeline_tag: text-classification
license: cc-by-sa-4.0
tags:
- populism
- politics
model-index:
- name: coastalcph/roberta-large-ft-trump-populism
  results: []
widget:
- text: >-
    Most importantly, we are going to take power back from the political class in Washington and return that power to you, the American people.
- text: >-
    She's totally bought and paid for by Wall Street, the special interests, the lobbyists, 100 percent.
datasets:
- coastalcph/populism-trump-2016
base_model:
- FacebookAI/roberta-large
---

# RoBERTa (Large) fine-tuned on Donald Trump's speeches with populism tags

This model is released as part of "Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns" ([Chalkidis et al., 2025](https://arxiv.org/abs/2507.19303)).
The model was fine-tuned from RoBERTa large (https://huggingface.co/FacebookAI/roberta-large) using the Donald Trump Populism 2016 dataset (https://huggingface.co/datasets/coastalcph/populism-trump-2016).

## Intended uses & limitations

The intended use is for academic research for the identification of fine-grained forms of populism

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- seed: 42
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- n_epochs: 3

### Framework versions

- Transformers 4.33.1
- Pytorch 1.12.0+cu102
- Datasets 2.14.5
- Tokenizers 0.13.3

## Citation Information

*[Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns. 
Ilias Chalkidis, Stephanie Brandl, and Paris Aslanidis. 
Arxiv Preprint, 2025.](https://arxiv.org/abs/2507.19303)*

```
@misc{chalkidis-et-al-2025-populism,
    title = "Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump’s Presidential Campaigns",
    author = "Chalkidis, Ilias and Brandl, Stephanie and Aslanidis, Paris",
    year = "2025",
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2507.19303}
}

```