Common Sense Reasoning On Swag
Metrics
Test
Results
Performance results of various models on this benchmark
Model Name | Test | Paper Title | Repository |
|---|---|---|---|
| RoBERTa | 89.9 | RoBERTa: A Robustly Optimized BERT Pretraining Approach | |
| ESIM + GloVe | 52.7 | SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference | |
| ESIM + ELMo | 59.2 | SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference | |
| BERT-LARGE | 86.3 | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding | |
| DeBERTalarge | 90.8 | DeBERTa: Decoding-enhanced BERT with Disentangled Attention |
0 of 5 row(s) selected.