README.md

---
license: cc-by-4.0
language: en
base_model: roberta-base
pipeline_tag: text-classification
tags: [literary-studies, embodiment, narrative, digital-humanities]
---

# Embodiment Classifier (English narrative fiction)

Sentence-level classifier assigning one of 11 embodiment categories to sentences
from English-language prose fiction. Fine-tuned from `roberta-base`.

Labels: `no_rel`, `character_move`, `haptic_material`, `character_feltness`,
`facial_expr`, `sight_human`, `book_paratext`, `haptic_human_animal`,
`sight_material`, `segmentation_error`, `gesture`.

## Usage

```python
from transformers import pipeline
clf = pipeline("text-classification", model="katrohrb/embodiment-classifier")
clf("She reached out and touched the rough bark.")
# -> [{'label': 'haptic_material', ...}]
```


## Performance

Held-out test set (n=580): micro-F1 **0.805** [0.772, 0.835], macro-F1 0.797.
5-fold CV: 0.808 +/- 0.022. Human inter-annotator agreement ceiling: Cohen's kappa 0.760.

## Data and code

Codebook, gold annotations, and reproduction notebooks:
https://github.com/katrin-rohrbacher/embodiment-paper

## Citation

<Add the bibliographic reference once the paper is out.>