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deberta-v3-base-ECE
akira225/deberta-v3-base-ECE
deberta-v3-base-ECE is a token classification model from akira225. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
This is DeBERTa-v3 fine-tuned for Emotion Cause Extraction (ECE) task. For input text i.e. a sequence of tokens containing a situation with emotional coloring, it is necessary to determine the subset of which tokens j…
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- deberta-v2
- Access
- Public
- Created
- Jun 21, 2023
- Updated
- Jun 21, 2023
- SHA
- 0c1edcb2
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Model card
From the Hugging Face model README
Model Card for DeBERTa-v3-base-ECE
This is DeBERTa-v3 fine-tuned for Emotion Cause Extraction (ECE) task. For input text i.e. a sequence of tokens containing a situation with emotional coloring, it is necessary to determine the subset of which tokens justify the emotional state of the speaker. Formally speaking, it is convenient to look at the problem as a binary token classification, where one means that the corresponding token belongs to the desired subset.
Training
Code use to train this model avaliable on my GitHub
Evaluation
Has following results on EmoCause and EmpatheticDialodues:
| Accuracy | Top-1 Recall | Top-3 Recall | Top-5 Recall |
|---|---|---|---|
| 0.59 | 0.249 | 0.623 | 0.806 |
- Task
- Token Classification
- Library
- transformers
- Type
- deberta-v2
- License
- apache-2.0
- Languages
- en
- Created
- Jun 21, 2023
- Updated
- Jun 21, 2023