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This is a BERTweet-base model that has been further pre-trained with preferential masking of emotion words for 100k steps on about 6.3M Vent posts.
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This model is meant to be fine-tuned on labeled data or used as feature extractor for downstream tasks.
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This is a BERTweet-base model that has been further pre-trained with preferential masking of emotion words for 100k steps on about 6.3M Vent posts.
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This model is meant to be fine-tuned on labeled data or used as feature extractor for downstream tasks.
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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={arXiv preprint arXiv:2304.10973},
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year={2023}
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}
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```
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