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license: cc-by-sa-4.0 |
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--- |
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# CamemBERT-EmoTextToKids |
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Classification model for |
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- input: a sentence + the previous and following sentences |
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- output: 20 labels |
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- is emotional |
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- mode of expression |
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- type of emotion(s) (basic, complex) |
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- category of emotion(s) |
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## Input format |
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The prompt template is: |
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```before:{previous_sentence}</s>current: {target_sentence}</s>after:{next_sentence}</s>``` |
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## Output format |
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Labels are returned in the following order: |
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0. sentence is emotional |
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1. mode is behavioral |
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2. mode is labeled |
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3. mode is displayed |
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4. mode is suggested |
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5. type is basic |
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6. type is complex |
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7. category is admiration |
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8. category is other |
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9. category is anger |
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10. category is guilt |
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11. category is disgust |
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12. category is embarassement |
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13. category is pride |
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14. category is jealousy |
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15. category is fear |
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16. category is joy |
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17. categoy is fear |
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18. category is surprise |
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19. category is sadness |
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See the [original paper](https://arxiv.org/pdf/2405.14385) for details about training. |
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## Dataset |
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See [EmoTextToKids-sentences](https://huggingface.co/datasets/TextToKids/EmoTextToKids-sentences) |
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## Citation information |
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```bibtex |
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@inproceedings{etienne2024emotion, |
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title={Emotion Identification for French in Written Texts: Considering Modes of Emotion Expression as a Step Towards Text Complexity Analysis}, |
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author={{\'E}tienne, Aline and Battistelli, Delphine and Lecorv{\'e}, Gw{\'e}nol{\'e}}, |
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booktitle={Proceedings of the 14th ACL Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA)}, |
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year={2024} |
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} |
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``` |
