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Natural Language Understanding on SuperGLUE (dev)

93.2Average ScoreST-MoE 32B
50.35261.47672.683.724Mar 18, 2021Jul 31, 2021Dec 14, 2021Apr 29, 2022Sep 12, 2022Jan 26, 2023Jun 11, 2023

Evaluation results

MethodLinks
ST-MoE 32BTotal Parameters=269B, Effective Parameters=32B, Evaluation Protocol=Finetuned2022.0593.295.793.1—1001008110095—10090.469.995.6—
ST-MoE-32BModel Parameters=32B2022.0493.295.793.1—1001008110095—10090.469.995.6—
PaLM 540BParameters=540B, Evaluation Protocol=Finetuned2022.0592.695.792.2—10010078.810094—10090.169.294.6—
PaLM 540BModel Parameters=540B, Evaluation Protocol=finetuned2022.0492.695.792.2—10010078.810094—10090.169.294.6—
UL2 20BParameters=20B, Evaluation Protocol=Finetuned2022.0590.792.190.8—9998.777.398.193.7—98.288.464.893.2—
T5 11BParameters=11B, Evaluation Protocol=Finetuned2022.0589.993.990.8—9894.977.396.293.8—96.487.466.193.2—
T5-11BModel Parameters=11B2022.0489.993.990.8—9894.977.396.293.8—96.487.466.193.2—
PaLM 62BParameters=62B, Evaluation Protocol=Finetuned2022.0589.289.590.6—9896.475.996.293—95.787.761.992.4—
GLMTeacher Scale=T32023.0689——————————————
GLMD-vcTeacher-Student Scale=T3-S3, Student parameters=2B, Excludes=ReCoRD2023.0684.76——————————————
PaLM 8BParameters=8B, Evaluation Protocol=Finetuned2022.0583.484.587.6—8696.473.488.589.7—92.181.66489.3—
GLM_RoBERTaPre-trained corpora=Larger corpora2021.0382.987.784.7—8298.271.283.789.68998.782.450.1——
RoBERTa_LargePre-trained corpora=Larger corpora2021.0381.58786.1—9094.672.663.58988.496.184.452.9——
T5_LargePre-trained corpora=Larger corpora2021.0381.284.884.3—7898.271.684.685.78596.480.946.6——
GLM_515MPre-trained corpora=BookCorpus and Wikipedia, Backbone Scale=1.5x BERT_Large2021.0378.879.181.3—8596.469.481.782.381.79577.235——
PaLM 540BEvaluation Mode=Zero-shot2022.0878.872.988—9351.859.189.1—92.9—83.5———
GLM_410MPre-trained corpora=BookCorpus and Wikipedia, Backbone Scale=1.25x BERT_Large2021.037879.481.9—8096.46981.781.580.993.276.235.5——
GLMTeacher Scale=T22023.0677.1——————————————
GLM_LargePre-trained corpora=BookCorpus and Wikipedia2021.03777482.1—7694.668.581.781.781.196.177.136.3——
GLM_SentPre-trained corpora=BookCorpus and Wikipedia2021.0376.879.180.8—7793.770.479.880.780.294.676.936.1——
T5_BasePre-trained corpora=Larger corpora2021.037678.380.8—7392.967.979.876.275.494.876.440——
BART_LargePre-trained corpora=Larger corpora2021.037684.584.3—6092.96965.488.387.890.581.848——
GLM_DocPre-trained corpora=BookCorpus and Wikipedia2021.0375.776.279.8—7796.463.678.880.279.697.374.632.1——
UniLM_LargePre-trained corpora=BookCorpus and Wikipedia2021.0374.176.580.5—7291.169.765.48079.19177.238.2——
GLMDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=55M2023.0672.2——————————————
GLMD-vcTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0672.1——————————————
BERT_LargePre-trained corpora=BookCorpus and Wikipedia2021.037273.680.1—6992.97164.476.375.694.871.924.1——
GLMTeacher Scale=T12023.0671.7——————————————
GLMD-vcTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0671.5——————————————
GLMDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=55M2023.0670.9——————————————
TinyBERTTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0670.8——————————————
GLM_BasePre-trained corpora=BookCorpus and Wikipedia2021.0370.771.277—7185.764.772.173.572.889.572.126.1——
AlexaTM 20BEvaluation Mode=Zero-shot2022.0869.1668.5969.44—7867.953.2968.27—88.4—59.57———
TinyBERTTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0669.1——————————————
GLMD-vcTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0667.9——————————————
GLMDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=16M2023.0667.4——————————————
GLMD+alTeacher-Student Scale=T1-S1, rv=0.5, Student parameters=14M2023.0667.4——————————————
TinyBERTTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0667.3——————————————
GLMD-vc+alTeacher-Student Scale=T1-S1, rv=0.5, Student parameters=16M2023.0667.3——————————————
GLMD-vc+moTeacher-Student Scale=T1-S1, rv=0.5, Student parameters=16M2023.0667——————————————
DIITOTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0666.8——————————————
PKDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0666.2——————————————
Universal-KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0666.2——————————————
BERT_BasePre-trained corpora=BookCorpus and Wikipedia2021.0366.17074.9—6676.868.865.465.464.970.968.421.5——
TheseusTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0666.1——————————————
MiniLMv2Teacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0666.1——————————————
TMKDTeacher-Student Scale=(T1, T2)-S2, Student parameters=66M2023.0665.6——————————————
UncertaintyTeacher-Student Scale=(T1, T2)-S2, Student parameters=66M2023.0665.4——————————————
RL-KDTeacher-Student Scale=(T1, T2)-S2, Student parameters=66M2023.0665.3——————————————
MobileBERT25MTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0665.1——————————————
TinyBERTTeacher-Student Scale=T3-S3, Student parameters=2B, Excludes=ReCoRD2023.0665.09——————————————
ALP-KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0664.3——————————————
DistilBERTTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.8——————————————
MiniLMTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.8——————————————
MiniLMv2Teacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.7——————————————
RAIL-KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.6——————————————
MGSKDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.5——————————————
Annealing-KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.3——————————————
CKDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0663.3——————————————
Annealing-KDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0663.1——————————————
UL 20BEvaluation Mode=Zero-shot2022.086360.763.1—8541.149.879.9—88.1—36.2———
Continuation-KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0662.7——————————————
CKDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0662.6——————————————
MiniLMTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0662.4——————————————
LRC-BERTTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0662.3——————————————
MiniLMv2Teacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0662.1——————————————
PDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0662——————————————
CKDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661.9——————————————
Continuation-KDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0661.7——————————————
MiniLMTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661.6——————————————
PDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0661.4——————————————
RAIL-KDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661.2——————————————
GPT3 175BEvaluation Mode=Zero-shot2022.0861.263.560.5—9146.4065.4—90.2—72.9———
PDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661——————————————
Annealing-KDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661——————————————
Continuation-KDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0661——————————————
LRC-BERTTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0660.8——————————————
RAIL-KDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0660.4——————————————
MGSKDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0659.9——————————————
MT-BERTTeacher-Student Scale=(T1, T2)-S2, Student parameters=66M2023.0659.1——————————————
MGSKDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0658.8——————————————
LRC-BERTTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0658.4——————————————
GPT3 13BEvaluation Mode=Zero-shot2022.0857.262.866.2—8419.6064.4—89—71.4———
SIDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0655.1——————————————
Universal-KDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0654.5——————————————
TAKDTeacher-Student Scale=T2-A1-A2-S2, Student parameters=66M2023.0654.5——————————————
DGKDTeacher-Student Scale=T2-A1-A2-S2, Student parameters=66M2023.0654——————————————
KDTeacher-Student Scale=T2-S2, Compression ratio=0.2, Student parameters=66M2023.0653.2——————————————
Universal-KDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0652.9——————————————
KDTeacher-Student Scale=T1-S2, Compression ratio=0.5, Student parameters=66M2023.0652.4——————————————
KDTeacher-Student Scale=T1-S1, Compression ratio=0.2, Student parameters=22M2023.0652——————————————
BasedArchitecture=Based, shots=1-shot2024.02—47.648.3—66—46.555.862.7————62.151.5
BaselineBackbone=BERT-large2023.05——78.1—7291.1—————70.3———
BaselineBackbone=BERT-base2023.05——74.4—6383.9—————68.1———
BLOOM 175BEvaluation Mode=Zero-shot2022.08—5263.5—5633.950.651.9———57.1———
E-LANGArchitecture=T5, Super model=T5-11B, Swift model=T5-Large, Avg. Speed-up (FLOPs)=2.9X, Avg. Speed-up (time)=2.0X2022.03—93.288.784.99093.178.189.4———————
ReBasedArchitecture=ReBased, shots=1-shot2024.02—53.152—67—46.956.762.8————62.251.9
SCTDBackbone=BERT-large2023.05——79.7—7292.9—————72.8———
SCTDBackbone=BERT-base2023.05——73.8—6887.5—————68.9———
Super (11B)Architecture=T5-11B, FLOPs=87e112022.03—93.189.484.99393.177.489.4———————