bert_v1

Reported on 7 benchmarks across 1 task

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing7 results

Visual Question Answering (VQA)onGQA Test2019
Accuracy
60.37
best: 89.3 (human)
Visual Question Answering (VQA)onGQA Test2019
Binary
77.09
best: 91.2 (human)
Visual Question Answering (VQA)onGQA Test2019
Consistency
89.77
best: 98.4 (human)
Visual Question Answering (VQA)onGQA Test2019
Distribution
6.43
best: 93.08 (GlobalPrior)
Visual Question Answering (VQA)onGQA Test2019
Open
45.61
best: 87.4 (human)
Visual Question Answering (VQA)onGQA Test2019
Plausibility
84.56
best: 97.2 (human)
Visual Question Answering (VQA)onGQA Test2019
Validity
96.22
best: 98.9 (human)