Question Answering On Race
Métriques
RACE
RACE-h
RACE-m
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | RACE | RACE-h | RACE-m | Paper Title | Repository |
|---|---|---|---|---|---|
| OCN_large | 71.7 | 69.6 | 76.7 | Option Comparison Network for Multiple-choice Reading Comprehension | - |
| XLNet | 81.75 | - | 85.45 | XLNet: Generalized Autoregressive Pretraining for Language Understanding | |
| DCMN_large | 69.7 | 68.1 | 73.4 | Dual Co-Matching Network for Multi-choice Reading Comprehension | - |
| GPT-3 175B (few-shot, k=32) | - | - | 58.1 | Language Models are Few-Shot Learners | |
| Finetuned Transformer LM | 59.0 | 57.4 | 62.9 | Improving Language Understanding by Generative Pre-Training | |
| BiAttention MRU | 53.3 | 50.3 | 60.2 | Multi-range Reasoning for Machine Comprehension | - |
| GPT-3 175B (Few-Shot) | - | 46.8 | - | Language Models are Few-Shot Learners |
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