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Lora · 10 rows

Model_name stringclasses 10 values	Train_size int64 50.8k 50.8k	Test_size int64 12.7k 12.7k	lora listlengths 2 9	Trainable_parameters int64 21.2M 139M	r int64 80 128	Memory Allocation stringclasses 10 values	accuracy float64 88.3 89.9	f1_macro float64 87.7 89.5	f1_weighted float64 88.3 89.9	precision float64 87.7 89.6	recall float64 87.7 89.5
FacebookAI/roberta-large	50,775	12,652	[ "dense", "value", "out_proj", "key", "query" ]	57,686,029	128	1250.26	89.89883	89.534963	89.911048	89.576317	89.508516
FacebookAI/xlm-roberta-large	50,775	12,652	[ "dense", "value", "out_proj", "key", "query" ]	36,452,365	80	1128.45	89.685425	89.260193	89.70282	89.401579	89.144042
Qwen/Qwen3-Reranker-0.6B	50,775	12,652	[ "down_proj", "gate_proj", "o_proj", "score", "up_proj" ]	41,300,992	96	4237.79	88.966171	88.356148	88.985935	88.46872	88.281362
RUCAIBox/mvp	50,775	12,652	[ "fc1", "dense", "k_proj", "out_proj", "q_proj", "fc2", "v_proj" ]	69,600,896	128	1616.52	89.685425	89.191071	89.700643	89.293141	89.107709
answerdotai/ModernBERT-large	50,775	12,652	[ "classifier", "Wqkv", "dense", "Wo", "Wi" ]	50,619,405	112	1411.06	89.574771	88.993892	89.587722	89.168306	88.847172
facebook/bart-large	50,775	12,652	[ "v_proj", "fc2", "out_proj", "fc1", "dense", "q_proj", "k_proj" ]	69,600,896	128	1974.07	89.693329	89.205372	89.704545	89.288181	89.150289
facebook/opt-125m	50,775	12,652	[ "v_proj", "fc2", "out_proj", "score", "fc1", "q_proj", "k_proj" ]	21,243,648	128	630.39	88.318052	87.702751	88.341254	87.74554	87.682287
facebook/opt-350m	50,775	12,652	[ "v_proj", "fc2", "out_proj", "score", "project_in", "fc1", "q_proj", "k_proj", "project_out" ]	57,022,976	128	1649.96	89.037306	88.618297	89.044621	88.733269	88.516525
google-bert/bert-large-uncased	50,775	12,652	[ "classifier", "dense" ]	38,024,205	128	1188.62	88.721151	88.122461	88.749407	88.242394	88.043566
google-t5/t5-large	50,775	12,652	[ "wi", "out_proj", "dense", "o", "wo", "v", "q", "k" ]	138,806,912	128	4038.77	89.037306	88.276916	89.050665	88.603012	88.031521

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