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--- |
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license: mit |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-classification |
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widget: |
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- text: "You wont believe what happened to me today" |
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- text: "You wont believe what happened to me today!" |
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- text: "You wont believe what happened to me today..." |
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- text: "You wont believe what happened to me today <3" |
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- text: "You wont believe what happened to me today :)" |
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- text: "You wont believe what happened to me today :(" |
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--- |
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This is an emotion classification model based on further pre-training of BERTweet-base with preferential masking of emotion words and fine-tuning on a subset of a self-labeled emotion dataset (Lykousas et al., 2019) that corresponds to Anger, Fear, Sadness, Joy, and Affection. The paper, [LEIA: Linguistic Embeddings for the Identification of Affect](https://doi.org/10.1140/epjds/s13688-023-00427-0) provides further details on the model and its evauation. |
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See [LEIA-large](https://huggingface.co/LEIA/LEIA-large) for a similar model based on BERTweet-large. |
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## Citation |
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Please cite the following paper if you find the model useful for your work: |
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```bibtex |
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@article{aroyehun2023leia, |
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title={LEIA: Linguistic Embeddings for the Identification of Affect}, |
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author={Aroyehun, Segun Taofeek and Malik, Lukas and Metzler, Hannah and Haimerl, Nikolas and Di Natale, Anna and Garcia, David}, |
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journal={EPJ Data Science}, |
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volume={12}, |
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year={2023}, |
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publisher={Springer} |
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} |
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``` |
