

<!-- Provide a quick summary of what the model is/does. -->

RoBERTa Large trained on Social Interaction QA dataset using HuggingFace's Script for training Multiple Choice QA models.
The model was trained for the EACL 2023 paper: MetaQA: Combining Expert Agents for Multi-Skill Question Answering. More information on: https://arxiv.org/abs/2112.01922
The average performance of five models trained with different random seeds on the on the test set is 74.17 ± 0.64
{"language": ["en"], "datasets": ["social_i_qa"], "metrics": ["accuracy"]}
transformers pytorch roberta multiple-choice en dataset:social_i_qa arxiv:2112.01922 endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #multiple-choice #en #dataset-social_i_qa #arxiv-2112.01922 #endpoints_compatible #region-us 





RoBERTa Large trained on Social Interaction QA dataset using HuggingFace's Script for training Multiple Choice QA models.
The model was trained for the EACL 2023 paper: MetaQA: Combining Expert Agents for Multi-Skill Question Answering. More information on: URL
The average performance of five models trained with different random seeds on the on the test set is 74.17 ± 0.64
TAGS
#transformers #pytorch #roberta #multiple-choice #en #dataset-social_i_qa #arxiv-2112.01922 #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #roberta #multiple-choice #en #dataset-social_i_qa #arxiv-2112.01922 #endpoints_compatible #region-us 
