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Mitigating a language model's over-confidence with NLI predictions on Multi-NLI hypotheses with random word order using PAWS (paraphrase) and Winogrande (anaphora).

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winogrande_1.1
winogrande_1.1
 
 
RD.ipynb
RD.ipynb
 
 
README.md
README.md
 
 
hans.zip
hans.zip
 
 
mnli.zip
mnli.zip
 
 
paws.zip
paws.zip
 
 
randoms.zip
randoms.zip
 
 
rnd_eval.py
rnd_eval.py
 
 
rnd_train.py
rnd_train.py
 
 
winogrande.zip
winogrande.zip
 
 

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Additional Paraphrase Training Drives Language Models Closer to Human Behaviour on Natural Language Inference

A Research and Development project.

Refer to the Jupyter notebook for now.

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Mitigating a language model's over-confidence with NLI predictions on Multi-NLI hypotheses with random word order using PAWS (paraphrase) and Winogrande (anaphora).

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language-model natural-language-inference classification-model paws nli roberta huggingface mnli-dataset winogrande roberta-base

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