Natural Language Understanding on GLUE (val)
97.4SST-2RoBERTa-Large + MUPPET
Evaluation Results
| Method | Links | |||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RoBERTa-Large + MUPPETModel Architecture=RoBERTa-Large, Pre-finetuning=MUPPET2021.01 | 97.4 | 90.8 | — | 94.9 | 92.2 | — | 92.8 | 91.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Factor-wise MuonMomentum=Without momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 97.25 | — | 82.35 | 94.47 | — | — | 84.12 | — | — | 88.42 | — | 69.32 | — | — | 89.77 | — | — | — | — | — | 84.39 | 81.68 | — | — | — | — | — | 45.07 | — | |
| Scaled AdamWMomentum=With momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 97.25 | — | 89.46 | 94.67 | — | — | 91.34 | — | — | 92.22 | — | 71.3 | — | — | 90.68 | — | — | — | — | — | 91.1 | 89.01 | — | — | — | — | — | 83.1 | — | |
| iMuonMomentum=With momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 97.13 | — | 88.97 | 93.45 | — | — | 89.53 | — | — | 91.55 | — | 70.32 | — | — | 89.93 | — | — | — | — | — | 92.37 | 88.33 | — | — | — | — | — | 81.69 | — | |
| iMuonMomentum=Without momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 97.02 | — | 85.54 | 94.6 | — | — | 88.09 | — | — | 87.86 | — | 70.21 | — | — | 89.29 | — | — | — | — | — | 88.99 | 86.25 | — | — | — | — | — | 74.65 | — | |
| MATBackbone=RoBERTa-Large, Number of layers=24, Na=22020.06 | 97 | 90.7 | 91.9 | 95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BART + MUPPETModel Architecture=BART, Pre-finetuning=MUPPET2021.01 | 96.9 | 89.9 | — | 94.6 | 92.7 | — | 92.4 | 92.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ELECTRA-LargeModel Architecture=ELECTRA-Large2021.01 | 96.9 | 90.9 | — | 95 | 92.4 | — | 88 | 90.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Scaled GDMomentum=Without momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.9 | — | 81.62 | 94.4 | — | — | 54.15 | — | — | 91.15 | — | 68.17 | — | — | 90.21 | — | — | — | — | — | 90.31 | 80.36 | — | — | — | — | — | 56.34 | — | |
| Riemannion (SGD)Momentum=Without momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.9 | — | 82.6 | 94.93 | — | — | 82.67 | — | — | 87.77 | — | 68.9 | — | — | 91.55 | — | — | — | — | — | 77.99 | 82.65 | — | — | — | — | — | 60.56 | — | |
| Factor-wise MuonMomentum=With momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.9 | — | 89.71 | 94.97 | — | — | 89.89 | — | — | 91.74 | — | 71.45 | — | — | 91.29 | — | — | — | — | — | 92.18 | 88.56 | — | — | — | — | — | 78.87 | — | |
| RoBERTa + LayerDropBackbone=RoBERTa-Large, Number of layers=242020.06 | 96.8 | 90.1 | 91 | 94.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| AdamWMomentum=With momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.79 | — | 88.48 | 94.42 | — | — | 90.61 | — | — | 91.24 | — | 71.05 | — | — | 89.86 | — | — | — | — | — | 90.42 | 88.28 | — | — | — | — | — | 81.69 | — | |
| RoBERTa-Base + MUPPETModel Architecture=RoBERTa-Base, Pre-finetuning=MUPPET2021.01 | 96.7 | 88.1 | — | 93.3 | 91.9 | — | 87.8 | 91.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BARTModel Architecture=BART, Pre-finetuning=Standard2021.01 | 96.6 | 89.9 | — | 94.9 | 92.5 | — | 87 | 90.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Riemannion (Adam)Momentum=With momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.44 | — | 79.9 | 94.55 | — | — | 80.87 | — | — | 90.36 | — | 67 | — | — | 91.21 | — | — | — | — | — | 62.13 | 82.84 | — | — | — | — | — | 83.1 | — | |
| RoBERTaBackbone=RoBERTa-Large, Number of layers=242020.06 | 96.4 | 90.2 | 90.9 | 94.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RoBERTa-LargeModel Architecture=RoBERTa-Large, Pre-finetuning=Standard2021.01 | 96.4 | 90.2 | — | 94.7 | 92.2 | — | 88.1 | 90.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Full FT#Params=184M, Backbone=DeBERTa-v3-base2024.08 | 96.33 | — | 89.95 | 94.24 | — | — | 83.75 | — | — | 92.11 | — | 71.43 | — | — | 90.34 | — | — | — | — | — | 91.04 | 88.65 | — | — | — | — | — | — | — | |
| BA-LoRA#Params=1.33M, Backbone=DeBERTa-v3-base2024.08 | 96.25 | — | 92.11 | 95.35 | — | — | 88.58 | — | — | 93.63 | — | 75.46 | — | — | 91.26 | — | — | — | — | — | 92.71 | 90.67 | — | — | — | — | — | — | — | |
| AdaLoRA#Params=1.27M, Backbone=DeBERTa-v3-base2024.08 | 96.18 | — | 90.81 | 94.68 | — | — | 87.78 | — | — | 92.37 | — | 71.64 | — | — | 90.87 | — | — | — | — | — | 91.97 | 89.54 | — | — | — | — | — | — | — | |
| AdaptersNumber of Parameters=3.0M2023.05 | 96.1 | — | 90.2 | 94.8 | — | — | 83.8 | — | — | 91.9 | — | 68.3 | — | — | 90.2 | — | — | — | — | — | 92.1 | 88.4 | — | — | — | — | — | — | — | |
| SGDMomentum=Without momentum, Backbone=Mistral-7B, Quantization=4-bit, LoRA rank=162026.05 | 96.1 | — | 70.1 | 94.22 | — | — | 50.9 | — | — | 88.59 | — | 55.89 | — | — | 88.15 | — | — | — | — | — | 47.64 | 71.21 | — | — | — | — | — | 49.3 | — | |
| FFTNumber of Parameters=355M2023.05 | 96 | — | 89.2 | 94.6 | — | — | 85.2 | — | — | 91.6 | — | 66.8 | — | — | 90.6 | — | — | — | — | — | 91.5 | 88.2 | — | — | — | — | — | — | — | |
| WARPNumber of Parameters=25k2023.05 | 96 | — | 90.8 | 93.5 | — | — | 75.8 | — | — | 84.5 | — | 60.6 | — | — | 88.2 | — | — | — | — | — | 88.6 | 84.8 | — | — | — | — | — | — | — | |
| S-MaMNumber of Parameters=3.4M2023.05 | 95.9 | — | 90.4 | 94.5 | — | — | 85.2 | — | — | 90.6 | — | 66.3 | — | — | 90.6 | — | — | — | — | — | 91.6 | 88.1 | — | — | — | — | — | — | — | |
| DoRA#Params=1.27M, Backbone=DeBERTa-v3-base2024.08 | 95.85 | — | 91.04 | 94.21 | — | — | 86.19 | — | — | 92.34 | — | 71.03 | — | — | 90.48 | — | — | — | — | — | 91.92 | 89.13 | — | — | — | — | — | — | — | |
| PiSSA#Params=1.33M, Backbone=DeBERTa-v3-base2024.08 | 95.81 | — | 91.48 | 94.41 | — | — | 87.14 | — | — | 92.21 | — | 72.27 | — | — | 90.47 | — | — | — | — | — | 91.93 | 89.47 | — | — | — | — | — | — | — | |
| U-MaMNumber of Parameters=3.4M2023.05 | 95.8 | — | 90.7 | 94.1 | — | — | 85.9 | — | — | 90.8 | — | 66.8 | — | — | 90.3 | — | — | — | — | — | 91.8 | 88.3 | — | — | — | — | — | — | — | |
| LoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=68K, Data Distribution=i.i.d.2024.10 | 95.64 | — | — | 92.04 | — | — | — | — | — | 85.85 | — | — | — | — | 86.16 | — | — | — | — | — | — | 89.92 | — | — | — | — | — | — | — | |
| FedTT+Backbone=RoBERTa-Large, Parameter Count=28K, Data Distribution=i.i.d.2024.10 | 95.64 | — | — | 94.05 | — | — | — | — | — | 88.99 | — | — | — | — | 88.27 | — | — | — | — | — | — | 91.74 | — | — | — | — | — | — | — | |
| FedTT+Backbone=RoBERTa-Large, Parameter Count=28K, Data Distribution=mild heterogeneity2024.10 | 95.64 | — | — | 92.6 | — | — | — | — | — | 87.76 | — | — | — | — | 88.11 | — | — | — | — | — | — | 91.03 | — | — | — | — | — | — | — | |
| BitFitNumber of Parameters=273k2023.05 | 95.6 | — | 88.2 | 93.9 | — | — | 81.9 | — | — | 88.1 | — | 65 | — | — | 89.2 | — | — | — | — | — | 91.4 | 86.7 | — | — | — | — | — | — | — | |
| RoLoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=34K, Data Distribution=i.i.d.2024.10 | 95.6 | — | — | 91.62 | — | — | — | — | — | 85.66 | — | — | — | — | 86.16 | — | — | — | — | — | — | 89.76 | — | — | — | — | — | — | — | |
| U-BitFitNumber of Parameters=25k2023.05 | 95.5 | — | 85.3 | 93.5 | — | — | 74 | — | — | 87.7 | — | 62.1 | — | — | 88.8 | — | — | — | — | — | 90.3 | 84.6 | — | — | — | — | — | — | — | |
| FouRABase Model=RoBERTa, Number of seeds=32024.06 | 95.5 | — | 90.4 | 94.2 | — | — | — | — | — | — | — | 70.6 | — | — | 90.5 | — | — | — | — | — | 91.6 | — | — | — | — | — | — | — | — | |
| PAdapter#Params=1.18M, Backbone=DeBERTa-v3-base2024.08 | 95.49 | — | 89.71 | 94.38 | — | — | 85.53 | — | — | 92.15 | — | 69.04 | — | — | 90.42 | — | — | — | — | — | 91.69 | 88.55 | — | — | — | — | — | — | — | |
| ROBERTA_BASE + ContraNorm#Params=125M2023.12 | 95.41 | 87.88 | 93.17 | 92.82 | — | — | 80.51 | — | — | 88.91 | 87.4 | 63.06 | — | — | — | — | — | — | — | — | 90.34 | 86.61 | — | — | — | — | — | — | — | |
| ROBERTA_BASE + GFSA#Params=125M2023.12 | 95.41 | 87.99 | 93.52 | 92.97 | — | — | 80.14 | — | — | 89.09 | 87.54 | 64.11 | — | — | — | — | — | — | — | — | 90.35 | 86.79 | — | — | — | — | — | — | — | |
| HAdapter#Params=1.22M, Backbone=DeBERTa-v3-base2024.08 | 95.38 | — | 89.97 | 94.31 | — | — | 84.76 | — | — | 91.99 | — | 68.73 | — | — | 90.23 | — | — | — | — | — | 91.58 | 88.37 | — | — | — | — | — | — | — | |
| LoRANumber of Parameters=3.4M2023.05 | 95.3 | — | 89.7 | 93.8 | — | — | 84.8 | — | — | 90.3 | — | 65.1 | — | — | 90.7 | — | — | — | — | — | 91.7 | 87.7 | — | — | — | — | — | — | — | |
| MaMNumber of Parameters=3.4M2023.05 | 95.3 | — | 89.7 | 93.8 | — | — | 84.8 | — | — | 90.3 | — | 65.1 | — | — | 90.6 | — | — | — | — | — | 91.7 | 87.7 | — | — | — | — | — | — | — | |
| SORABase Model=RoBERTa, Number of seeds=32024.06 | 95.2 | — | 90.6 | 93.9 | — | — | — | — | — | — | — | 69.9 | — | — | 90.5 | — | — | — | — | — | 91.4 | — | — | — | — | — | — | — | — | |
| ELECTRA-BaseModel Architecture=ELECTRA-Base2021.01 | 95 | 88.8 | — | 93.2 | 91.5 | — | 82.7 | 89.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FNet-BaseModel Scale=Base, Hardware=TPU, Protocol=Fine-tuning2021.05 | 95 | 72 | 76 | 80 | — | — | 63 | — | — | 83 | 73 | 69 | — | — | — | — | — | — | — | — | 79 | 76.7 | — | — | — | — | — | — | — | |
| BERT-LargeModel Scale=Large, Hardware=TPU, Protocol=Fine-tuning2021.05 | 95 | 88 | 86 | 92 | — | — | 66 | — | — | 88 | 88 | 71 | — | — | — | — | — | — | — | — | 88 | 84.7 | — | — | — | — | — | — | — | |
| XLM-RSource=original XLM-R paper2026.01 | 95 | 88.9 | 89.5 | 93.8 | — | — | — | — | — | 92.3 | 89 | — | — | — | — | — | — | — | — | — | 91.2 | 91.8 | — | — | — | — | — | — | — | |
| FFA-LoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=34K, Data Distribution=i.i.d.2024.10 | 94.91 | — | — | 90.11 | — | — | — | — | — | 84.06 | — | — | — | — | 85.48 | — | — | — | — | — | — | 88.64 | — | — | — | — | — | — | — | |
| LoRABase Model=RoBERTa, Number of seeds=32024.06 | 94.9 | — | 90.3 | 93.6 | — | — | — | — | — | — | — | 67.3 | — | — | 90.2 | — | — | — | — | — | 89.9 | — | — | — | — | — | — | — | — | |
| ROBERTA_BASE#Params=125M2023.12 | 94.84 | 87.94 | 92.28 | 92.57 | — | — | 78.7 | — | — | 88.86 | 87.3 | 60.34 | — | — | — | — | — | — | — | — | 89.99 | 85.87 | — | — | — | — | — | — | — | |
| RoLoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=34K, Data Distribution=mild heterogeneity2024.10 | 94.84 | — | — | 90.77 | — | — | — | — | — | 85.13 | — | — | — | — | 85.1 | — | — | — | — | — | — | 88.96 | — | — | — | — | — | — | — | |
| RoBERTa-BaseModel Architecture=RoBERTa-Base, Pre-finetuning=Standard2021.01 | 94.8 | 87.6 | — | 92.8 | 91.9 | — | 78.7 | 90.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LoRA#Params=1.33M, Backbone=DeBERTa-v3-base2024.08 | 94.79 | — | 89.85 | 93.94 | — | — | 85.43 | — | — | 92.07 | — | 70.05 | — | — | 90.71 | — | — | — | — | — | 91.67 | 88.56 | — | — | — | — | — | — | — | |
| Full Fine-tuningBackbone=T5-base, Fine-tuning Protocol=Full-FT2024.07 | 94.75 | — | 84.56 | 93.19 | — | — | — | — | — | — | — | 80.7 | — | — | 86.33 | — | — | — | — | — | — | 87.91 | — | — | — | — | — | — | — | |
| LoRASpeedup=1×, Backbone=RoBERTa-base2025.12 | 94.72 | — | 86.76 | 92.53 | — | — | 77.61 | — | — | — | — | 59.56 | — | — | — | — | — | — | — | — | 90.81 | 83.67 | — | — | — | — | — | — | — | |
| BitFit#Params=0.1M, Backbone=DeBERTa-v3-base2024.08 | 94.68 | — | 87.95 | 92.45 | — | — | 79.12 | — | — | 88.72 | — | 67.31 | — | — | 89.54 | — | — | — | — | — | 91.63 | 86.43 | — | — | — | — | — | — | — | |
| FTnumber of parameters=220M, base model=T5-base2024.02 | 94.6 | — | 90.2 | 93 | — | — | 71.9 | — | — | 91.6 | — | 61.8 | — | — | 86.8 | — | — | — | — | — | 89.7 | 84.9 | — | — | — | — | — | — | — | |
| Full Fine-TuningBackbone=RoBERTa-Base2024.05 | 94.57 | — | 91.3 | 92.33 | — | — | 79.42 | — | — | 92.28 | — | 62.24 | — | — | 87.18 | — | — | — | — | — | 90.92 | 86.28 | — | — | — | — | — | — | 4.64 | |
| AdamBackbone=RoBERTa-base, Mode=Fine-tuning2025.01 | 94.57 | — | 92.25 | 92.18 | — | — | 79.06 | — | — | 92.28 | — | 63.81 | — | — | 87.29 | — | — | — | — | — | 91.26 | 86.58 | — | — | — | — | — | — | — | |
| LORABackbone=RoBERTa-Base, # Param.=0.30M2024.10 | 94.4 | — | 89.8 | 86 | — | — | — | — | — | 86.5 | — | — | — | — | 84.7 | — | — | — | — | — | — | 88.3 | — | — | — | — | — | — | — | |
| VeLORABackbone=RoBERTa-Base2024.05 | 94.38 | — | 91.26 | 92.09 | — | — | 77.98 | — | — | 89.91 | — | 64.56 | — | — | 86.29 | — | — | — | — | — | 90.81 | 85.91 | — | — | — | — | — | — | 2.23 | |
| FedTTBackbone=RoBERTa-Large, Parameter Count=51K, Data Distribution=i.i.d.2024.10 | 94.38 | — | — | 93.01 | — | — | — | — | — | 88.3 | — | — | — | — | 87.2 | — | — | — | — | — | — | 90.72 | — | — | — | — | — | — | — | |
| MT-DNN2021.01 | 94.3 | 87.1 | — | 92.9 | 91.9 | 89.2 | 83.4 | 91 | 87.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=68K, Data Distribution=mild heterogeneity2024.10 | 94.27 | — | — | 86.91 | — | — | — | — | — | 81.22 | — | — | — | — | 82.07 | — | — | — | — | — | — | 86.12 | — | — | — | — | — | — | — | |
| Universal order-3Speedup=1.8×, Backbone=RoBERTa-base2025.12 | 94.26 | — | 86.52 | 92.98 | — | — | 75.81 | — | — | — | — | 62.06 | — | — | — | — | — | — | — | — | 90.39 | 83.67 | — | — | — | — | — | — | — | |
| GWTBackbone=RoBERTa-base, Mode=Fine-tuning2025.01 | 94.26 | — | 93.26 | 92.53 | — | — | 79.42 | — | — | 91.94 | — | 62.57 | — | — | 87.37 | — | — | — | — | — | 91.16 | 86.56 | — | — | — | — | — | — | — | |
| Diff-Pruning% Param=0.5%, Source=Guo et al. (2020)2021.06 | 94.2 | 86.4 | 91.3 | 93.4 | — | — | 71.5 | — | — | 86.6 | 86.9 | 63.5 | — | — | — | 84.6 | — | — | — | — | 89.5 | — | — | — | — | — | — | — | — | |
| S-BitFitNumber of Parameters=25k2023.05 | 94.2 | — | 70.6 | 88.9 | — | — | 56 | — | — | 83.8 | — | 40.2 | — | — | 84.1 | — | — | — | — | — | 76.8 | 74.3 | — | — | — | — | — | — | — | |
| BitFitnumber of parameters=0.3M, base model=T5-base2024.02 | 94.2 | — | 86.8 | 93 | — | — | 67.6 | — | — | 90.1 | — | 58.2 | — | — | 85.3 | — | — | — | — | — | 90.9 | 83.3 | — | — | — | — | — | — | — | |
| rsLoRABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 94.19 | — | 52.86 | 93.12 | — | — | — | — | — | — | — | 72.32 | — | — | 85.73 | — | — | — | — | — | — | 79.64 | — | — | — | — | — | — | — | |
| BERT_BASE + GFSA#Params=110M2023.12 | 94.15 | 85.12 | 90.6 | 91.95 | — | — | 68.95 | — | — | 88.46 | 85.06 | 59.56 | — | — | — | — | — | — | — | — | 88.33 | 83.58 | — | — | — | — | — | — | — | |
| FedTTBackbone=RoBERTa-Large, Parameter Count=51K, Data Distribution=mild heterogeneity2024.10 | 94.15 | — | — | 91.38 | — | — | — | — | — | 86.25 | — | — | — | — | 86.53 | — | — | — | — | — | — | 89.58 | — | — | — | — | — | — | — | |
| Universal order-2Speedup=2×, Backbone=RoBERTa-base2025.12 | 94.15 | — | 87.25 | 92.71 | — | — | 77.62 | — | — | — | — | 61.82 | — | — | — | — | — | — | — | — | 90.48 | 84.01 | — | — | — | — | — | — | — | |
| LoRA-GABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 94.11 | — | 85.29 | 93.18 | — | — | — | — | — | — | — | 80.57 | — | — | 85.7 | — | — | — | — | — | — | 87.77 | — | — | — | — | — | — | — | |
| Full-FT% Param=100%, Source=Guo et al. (2020)2021.06 | 94.1 | 86.5 | 91.9 | 93.5 | — | — | 71.8 | — | — | 87.6 | 87.1 | 62.8 | — | — | — | 84.8 | — | — | — | — | 89.8 | — | — | — | — | — | — | — | — | |
| PISSABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 94.07 | — | 76.31 | 93.15 | — | — | — | — | — | — | — | 74.27 | — | — | 85.75 | — | — | — | — | — | — | 84.71 | — | — | — | — | — | — | — | |
| LoRABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 94.04 | — | 68.38 | 92.96 | — | — | — | — | — | — | — | 69.35 | — | — | 85.3 | — | — | — | — | — | — | 82.08 | — | — | — | — | — | — | — | |
| DoRABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 94.04 | — | 68.08 | 93.04 | — | — | — | — | — | — | — | 72.04 | — | — | 85.67 | — | — | — | — | — | — | 82.57 | — | — | — | — | — | — | — | |
| GaLoreBackbone=RoBERTa-Base2024.05 | 94.04 | — | 92.25 | 92.24 | — | — | 79.42 | — | — | 91.06 | — | 60.35 | — | — | 87 | — | — | — | — | — | 90.73 | 85.89 | — | — | — | — | — | — | 4.04 | |
| HYPERFORMER++_BASETraining Strategy=Multi-Task Training, #Total params=1.02x, #Trained params / per task=0.29%2021.06 | 94.03 | — | — | 93.02 | 90.28 | 87.2 | 75.36 | 89.66 | 92.63 | — | — | 63.73 | 90 | 89.66 | 85.74 | 86.48 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| GaLoreBackbone=RoBERTa-base, Mode=Fine-tuning2025.01 | 94.03 | — | 92.41 | 92.56 | — | — | 77.25 | — | — | 91.77 | — | 61.32 | — | — | 86.77 | — | — | — | — | — | 91.13 | 85.9 | — | — | — | — | — | — | — | |
| Linear-BaseModel Scale=Base, Hardware=TPU, Protocol=Fine-tuning2021.05 | 94 | 74 | 83 | 80 | — | — | 69 | — | — | 84 | 75 | 67 | — | — | — | — | — | — | — | — | 67 | 77 | — | — | — | — | — | — | — | |
| FNet-Hybrid-BaseModel Scale=Base, Hardware=TPU, Protocol=Fine-tuning2021.05 | 94 | 78 | 79 | 88 | — | — | 60 | — | — | 85 | 79 | 76 | — | — | — | — | — | — | — | — | 86 | 80.6 | — | — | — | — | — | — | — | |
| FNet-LargeModel Scale=Large, Hardware=TPU, Protocol=Fine-tuning2021.05 | 94 | 78 | 88 | 85 | — | — | 69 | — | — | 85 | 76 | 78 | — | — | — | — | — | — | — | — | 84 | 81.9 | — | — | — | — | — | — | — | |
| AdapterBackbone=RoBERTa-Base, # Param.=0.70M2024.10 | 94 | — | 88.5 | 85.9 | — | — | — | — | — | 87 | — | — | — | — | 84.9 | — | — | — | — | — | — | 88.1 | — | — | — | — | — | — | — | |
| BERT_BASE + ContraNorm#Params=110M2023.12 | 93.92 | 85.11 | 89.88 | 91.84 | — | — | 69.31 | — | — | 88.51 | 84.5 | 59.89 | — | — | — | — | — | — | — | — | 88.36 | 83.48 | — | — | — | — | — | — | — | |
| FFA-LoRABackbone=RoBERTa-Large, Rank=2, Parameter Count=34K, Data Distribution=mild heterogeneity2024.10 | 93.92 | — | — | 89.58 | — | — | — | — | — | 80.51 | — | — | — | — | 82.62 | — | — | — | — | — | — | 86.66 | — | — | — | — | — | — | — | |
| LoRA+Backbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 93.85 | — | 74.43 | 93.14 | — | — | — | — | — | — | — | 77.53 | — | — | 85.81 | — | — | — | — | — | — | 84.95 | — | — | — | — | — | — | — | |
| BERT_BASE#Params=110M2023.12 | 93.81 | 84.96 | 88.7 | 91.63 | — | — | 66.06 | — | — | 88.32 | 84.15 | 56.79 | — | — | — | — | — | — | — | — | 88.16 | 82.51 | — | — | — | — | — | — | — | |
| HYPERFORMER_BASETraining Strategy=Multi-Task Training, #Total params=1.54x, #Trained params / per task=6.86%2021.06 | 93.8 | — | — | 92.79 | 90.13 | 87.18 | 78.26 | 90.64 | 93.33 | — | — | 61.32 | 89.55 | 89.03 | 86.33 | 86.58 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Adapternumber of parameters=1.9M, base model=T5-base2024.02 | 93.8 | — | 85.3 | 93.2 | — | — | 71.9 | — | — | 90.2 | — | 64 | — | — | 86.5 | — | — | — | — | — | 90.7 | 84.5 | — | — | — | — | — | — | — | |
| FedTTBackbone=RoBERTa-Base, # Param.=0.06M2024.10 | 93.8 | — | 88.9 | 88.9 | — | — | — | — | — | 86.2 | — | — | — | — | 84.2 | — | — | — | — | — | — | 88.4 | — | — | — | — | — | — | — | |
| PrefixBackbone=RoBERTa-Base, # Param.=3.50M2024.10 | 93.7 | — | 88.1 | 84.6 | — | — | — | — | — | 81.8 | — | — | — | — | 80.4 | — | — | — | — | — | — | 85.7 | — | — | — | — | — | — | — | |
| BERT + ContraNorm-Dnormalization=ContraNorm-D2023.03 | 93.69 | 85.24 | 91.78 | 91.95 | — | — | 70.04 | — | — | 88.36 | 85.19 | 62.08 | — | — | — | — | — | — | — | — | 89.59 | 84.21 | — | — | — | — | — | — | — | |
| ALBERT-baseModel=ALBERT-base2023.03 | 93.69 | 84.56 | 92.09 | 90.9 | — | — | 76.53 | — | — | 87.23 | 84.37 | 57.35 | — | — | — | — | — | — | — | — | 90.54 | 83.74 | — | — | — | — | — | — | — | |
| AdaLoRABackbone=T5-base, Fine-tuning Protocol=PEFT2024.07 | 93.69 | — | 68.14 | 91.66 | — | — | — | — | — | — | — | 69.16 | — | — | 85.45 | — | — | — | — | — | — | 81.62 | — | — | — | — | — | — | — | |
| AdapterDropnumber of parameters=1.1M, base model=T5-base2024.02 | 93.6 | — | 86.3 | 93.2 | — | — | 71.2 | — | — | 90.2 | — | 62.7 | — | — | 86.3 | — | — | — | — | — | 91.4 | 84.4 | — | — | — | — | — | — | — | |
| APOLLOBackbone=RoBERTa-base, Mode=Fine-tuning2025.01 | 93.57 | — | 92 | 92.27 | — | — | 78.33 | — | — | 91.85 | — | 61.07 | — | — | 87.21 | — | — | — | — | — | 90.7 | 85.87 | — | — | — | — | — | — | — | |
| Adapters_BASETraining Strategy=Single-Task Training, #Total params=1 + 8 × 0.01, #Trained params / per task=0.87%2021.06 | 93.46 | — | — | 92.26 | 90.94 | 88.01 | 68.84 | 88.18 | 91.55 | — | — | 59.49 | 87.44 | 87.18 | 86.38 | 84.88 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LoRA*Backbone=RoBERTa-base, Mode=Fine-tuning2025.01 | 93.46 | — | 91.9 | 92.25 | — | — | 79.06 | — | — | 91.22 | — | 61.83 | — | — | 86.94 | — | — | — | — | — | 90.8 | 85.93 | — | — | — | — | — | — | — |