Aniemore/cedr-m7
CEDR M7 Russian text emotion corpus, adapted to seven Aniemore classes. Provenance This corpus is not ours. It is an adaptation: the source is sagteam/cedr_v1, and Aniemore's contribution is remapping it onto the seven classes the rest of the library uses. Credit for the collection and the original annotation belongs to the CEDR authors. Splits Split Rows Mean words Longest train 7528 14.8 51 test 1882 14.6 43 Fields… See the full description on the dataset page: https://huggingface.co/datasets/Aniemore/cedr-m7.
CEDR M7
Russian text emotion corpus, adapted to seven Aniemore classes.
Provenance
This corpus is not ours. It is an adaptation: the source is `sagteam/cedr_v1`, and Aniemore's contribution is remapping it onto the seven classes the rest of the library uses. Credit for the collection and the original annotation belongs to the CEDR authors.
Splits
<img src="assets/classes.svg" alt="Class distribution" width="760">
Fields
Usage
from datasets import load_dataset
ds = load_dataset("Aniemore/cedr-m7")
print(ds["train"][0]["text"], ds["train"][0]["labels"])Limitations
disgust is effectively absent: 17 rows in train, 3 rows in test. Any per-class number for it is noise, and it drags macro averages down. The class distribution is otherwise heavily skewed toward neutral.
Citation
@misc{Aniemore,
author = {Артем Аментес, Илья Лубенец, Никита Давидчук},
title = {Открытая библиотека искусственного интеллекта для анализа и выявления эмоциональных оттенков речи человека},
year = {2022},
publisher = {Hugging Face},
journal = {Hugging Face Hub},
howpublished = {\url{https://huggingface.com/aniemore/Aniemore}},
email = {hello@socialcode.ru}
}Please also cite the original CEDR corpus, `sagteam/cedr_v1`.
License
MIT.