File size: 1,575 Bytes
e9d6d9a 66be999 e9d6d9a 66be999 5cd3c7e 66be999 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
---
license: cc-by-sa-4.0
---
# CamemBERT-EmoTextToKids
Classification model for
- input: a sentence + the previous and following sentences
- output: 20 labels
- is emotional
- mode of expression
- type of emotion(s) (basic, complex)
- category of emotion(s)
## Input format
The prompt template is:
```before:{previous_sentence}</s>current: {target_sentence}</s>after:{next_sentence}</s>```
## Output format
Labels are returned in the following order:
0. sentence is emotional
1. mode is behavioral
2. mode is labeled
3. mode is displayed
4. mode is suggested
5. type is basic
6. type is complex
7. category is admiration
8. category is other
9. category is anger
10. category is guilt
11. category is disgust
12. category is embarassement
13. category is pride
14. category is jealousy
15. category is fear
16. category is joy
17. categoy is fear
18. category is surprise
19. category is sadness
See the [original paper](https://arxiv.org/pdf/2405.14385) for details about training.
## Dataset
See [EmoTextToKids-sentences](https://huggingface.co/datasets/TextToKids/EmoTextToKids-sentences)
## Citation information
```bibtex
@inproceedings{etienne2024emotion,
title={Emotion Identification for French in Written Texts: Considering Modes of Emotion Expression as a Step Towards Text Complexity Analysis},
author={{\'E}tienne, Aline and Battistelli, Delphine and Lecorv{\'e}, Gw{\'e}nol{\'e}},
booktitle={Proceedings of the 14th ACL Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA)},
year={2024}
}
``` |