ELC-BERT-small 24M

Reported on 4 benchmarks across 2 tasks · 1 paper

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

Natural Language Processing4 results

Natural Language InferenceonRTE
Accuracy· 2023-11-03
55.4
best: 86.8 (PSQ (Chen et al., 2020))
Not all layers are equally as important: Every Layer Counts BERT arXiv:2311.02265
Natural Language InferenceonMultiNLI
Matched· 2023-11-03
79.2
best: 92.6 (Turing NLR v5 XXL 5.4B (fine-tuned))
Not all layers are equally as important: Every Layer Counts BERT arXiv:2311.02265
Natural Language InferenceonMultiNLI
Mismatched· 2023-11-03
79.9
best: 92.4 (Turing NLR v5 XXL 5.4B (fine-tuned))
Not all layers are equally as important: Every Layer Counts BERT arXiv:2311.02265
Linguistic AcceptabilityonCoLA
Accuracy· 2023-11-03
76.1
best: 82.7 (LTG-BERT-base 98M)
Not all layers are equally as important: Every Layer Counts BERT arXiv:2311.02265