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LoraMemory

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Model_name stringlengths 12 30	Train_size int64 50.8k 50.8k	Test_size int64 12.7k 12.7k	lora listlengths 2 9	r int64 64 128	Trainable_parameters int64 21.2M 264M	Memory Allocation float64 0.62 5.63	accuracy float64 0.8 89.9	f1_macro float64 0.79 89.5	f1_weighted float64 0.82 89.9	precision float64 0.81 89.6	recall float64 0.82 89.5
FacebookAI/roberta-large	50,775	12,652	[ "dense", "value", "out_proj", "key", "query" ]	128	57,686,029	1.220957	89.89883	89.534963	89.911048	89.576317	89.508516
FacebookAI/xlm-roberta-large	50,775	12,652	[ "dense", "value", "out_proj", "key", "query" ]	80	36,452,365	1.102002	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" ]	96	41,300,992	4.138467	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" ]	128	69,600,896	1.578633	89.685425	89.191071	89.700643	89.293141	89.107709
answerdotai/ModernBERT-large	50,775	12,652	[ "classifier", "Wqkv", "dense", "Wo", "Wi" ]	112	50,619,405	1.377988	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" ]	128	69,600,896	1.927803	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" ]	128	21,243,648	0.615615	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" ]	128	57,022,976	1.611289	89.037306	88.618297	89.044621	88.733269	88.516525
google-bert/bert-large-uncased	50,775	12,652	[ "classifier", "dense" ]	128	38,024,205	1.160762	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" ]	128	138,806,912	3.944111	89.037306	88.276916	89.050665	88.603012	88.031521
Qwen/Qwen2-1.5B	50,775	12,652	[ "down_proj", "gate_proj", "k_proj", "o_proj", "q_proj", "up_proj", "v_proj" ]	128	147,738,112	2.874775	0.866029	0.853751	0.870671	0.852995	0.871274
Qwen/Qwen3-1.7B	50,775	12,652	[ "down_proj", "gate_proj", "k_proj", "o_proj", "q_proj", "up_proj", "v_proj" ]	128	139,487,232	2.846445	0.813705	0.803528	0.818697	0.805926	0.827676
facebook/opt-2.7b	50,775	12,652	[ "fc1", "fc2", "k_proj", "out_proj", "q_proj", "v_proj" ]	64	94,405,120	2.932852	0.80343	0.792611	0.817475	0.813736	0.818266
tiiuae/Falcon3-3B-Base	50,775	12,652	[ "down_proj", "gate_proj", "o_proj", "up_proj" ]	128	121,150,464	2.625752	0.842792	0.829756	0.848151	0.830768	0.849633
Qwen/Qwen2.5-3B-Instruct	50,775	12,652	[ "down_proj", "gate_proj", "o_proj", "up_proj" ]	128	199,387,136	3.926855	0.865476	0.85332	0.87013	0.852328	0.871832
Qwen/Qwen3-Embedding-4B	50,775	12,652	[ "down_proj", "gate_proj", "o_proj", "up_proj" ]	128	200,573,440	4.614141	0.847297	0.835933	0.853349	0.838054	0.855377
Alibaba-NLP/E2Rank-4B	50,775	12,652	[ "down_proj", "gate_proj", "k_proj", "o_proj", "q_proj", "up_proj", "v_proj" ]	128	264,274,432	5.630898	0.848482	0.836983	0.853935	0.837632	0.856989

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