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ParaBERT
luciegaba/ParaBERT
ParaBERT is a sentence similarity model from luciegaba. Use it when you need a score for how close two texts are. It is set up for transformers.
- Model Name: ParaBERT - Description: A fine-tuned paraphrase identification model based on BERT - Author: Lucie Gabagnou, Armand L'Huillier, Yanis Rehoune, Ghiles Idris - Language: Pytorch
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At a glance
- Task
- Sentence Similarity
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Apr 2, 2023
- Updated
- Apr 5, 2023
- SHA
- 36135f7f
Datasets
Model card
From the Hugging Face model README
Model Card: Paraphrase Identification
Model Details
- Model Name: ParaBERT
- Description: A fine-tuned paraphrase identification model based on BERT
- Author: Lucie Gabagnou, Armand L'Huillier, Yanis Rehoune, Ghiles Idris
- Language: Pytorch
Intended Use
- Primary intended uses: This model is designed to identify whether two questions are paraphrases of each other.
- Primary intended users: This model is intended for use by NLP researchers and developers who are working on tasks related to paraphrase identification.
- Out-of-scope use cases: This model should not be used for tasks outside of paraphrase identification, or in situations where the input data may contain sensitive or confidential information.
Model Architecture and Training Data
- Model Architecture: BERT
- Training Data: https://huggingface.co/datasets/bigscience/P3/viewer/glue_qqp_same_thing/train (Only questions)
Evaluation Data and Results
- Evaluation Data: https://huggingface.co/datasets/bigscience/P3/viewer/glue_qqp_same_thing/test
- Metrics: Accuracy
- Results: 0.95
- Task
- Sentence Similarity
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Apr 2, 2023
- Updated
- Apr 5, 2023