qbao775
/

AMR-LE-DeBERTa-V2-XXLarge-Contraposition-Double-Negation-Implication-Commutative-Pos-Neg-1-3

Text Classification

logical-reasoning

logical-equivalence

constrastive-learning

Inference Endpoints

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qbao775 commited on May 28, 2023

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@@ -22,7 +22,7 @@ Project: https://github.com/Strong-AI-Lab/Logical-Equivalence-driven-AMR-Data-Au
 Leaderboard: https://eval.ai/web/challenges/challenge-page/503/leaderboard/1347
-In this repository, we upload the model weight which has been trained on the dataset that has the ratio of positive sample and negative sample as 1 and 3. We use AMR with four logical equivalence laws `(Contraposition law, Commutative law, Implication law, Double negation law)` to construct 4 different logical equivalence/inequivalence sentences.
 ## How to load the model weight?
 ```
 from transformers import AutoModel

 Leaderboard: https://eval.ai/web/challenges/challenge-page/503/leaderboard/1347
+In this repository, we upload the model weight which has been trained on the dataset that has the ratio of positive sample and negative sample as 1 and 3. We use AMR with four logical equivalence laws `(Contraposition law, Commutative law, Implication law, Double negation law)` to construct four different logical equivalence/inequivalence sentences.
 ## How to load the model weight?
 ```
 from transformers import AutoModel