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Model_name
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Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
1
9
Parameters
int64
127M
773M
Trainable_parameters
int64
89.1k
34.3M
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int64
12
12
Memory Allocation
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Performance
dict
FacebookAI/roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "dense", "out_proj" ]
361,878,151
6,504,058
12
861.55
944.16
{ "accuracy": 0.9023079355042681, "f1_macro": 0.8981383310429655, "f1_weighted": 0.9024026384186253, "precision": 0.8989143440905782, "recall": 0.8974826990201171 }
FacebookAI/roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "key", "query", "value" ]
361,789,005
6,414,912
12
796.16
914.56
{ "accuracy": 0.8970913689535251, "f1_macro": 0.8930208645280477, "f1_weighted": 0.8972884285482097, "precision": 0.8946730774708442, "recall": 0.8916849926294002 }
FacebookAI/roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "out_proj", "value", "dense", "key", "query" ]
368,293,063
12,918,970
12
1236.64
1559.21
{ "accuracy": 0.902466013278533, "f1_macro": 0.8980287925374486, "f1_weighted": 0.9026097725108932, "precision": 0.8993767956625794, "recall": 0.8970088891527042 }
FacebookAI/xlm-roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "dense", "out_proj" ]
566,408,839
6,504,058
12
844.92
985.25
{ "accuracy": 0.899778691116029, "f1_macro": 0.8959369828349334, "f1_weighted": 0.899953835349855, "precision": 0.8972773756467176, "recall": 0.8949705202443672 }
FacebookAI/xlm-roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "key", "query", "value" ]
566,319,693
6,414,912
12
796.39
961.9
{ "accuracy": 0.8956686689851406, "f1_macro": 0.8901198273274508, "f1_weighted": 0.895854898529847, "precision": 0.890775952850292, "recall": 0.8896250133721503 }
FacebookAI/xlm-roberta-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "out_proj", "value", "dense", "key", "query" ]
572,823,751
12,918,970
12
1238.33
1643.52
{ "accuracy": 0.8989883022447044, "f1_macro": 0.8949189419685657, "f1_weighted": 0.8991035757517423, "precision": 0.8968424376861895, "recall": 0.8934020182303709 }
Qwen/Qwen3-Reranker-0.6B
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "down_proj", "gate_proj", "o_proj", "score", "up_proj" ]
605,769,650
9,978,802
12
1744.48
1901.83
{ "accuracy": 0.9004110022130888, "f1_macro": 0.8958331592620664, "f1_weighted": 0.9005460270680516, "precision": 0.8976345671491439, "recall": 0.8943125023611375 }
Qwen/Qwen3-Reranker-0.6B
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k_proj", "q_proj", "v_proj" ]
603,274,912
7,484,064
12
1547.97
1657.66
{ "accuracy": 0.8969332911792602, "f1_macro": 0.8920121710906675, "f1_weighted": 0.8971332803970018, "precision": 0.8931318979332828, "recall": 0.8911735622846216 }
Qwen/Qwen3-Reranker-0.6B
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "q_proj", "o_proj", "down_proj", "v_proj", "up_proj", "k_proj", "score", "gate_proj" ]
613,253,714
17,462,866
12
2213.54
2695.08
{ "accuracy": 0.8996206133417641, "f1_macro": 0.8952066266741632, "f1_weighted": 0.8999246109136576, "precision": 0.8962149889427752, "recall": 0.8945848726627367 }
RUCAIBox/mvp
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "dense", "fc1", "fc2", "out_proj" ]
414,930,663
7,573,210
12
1220.62
1361.0
{ "accuracy": 0.9037306354726525, "f1_macro": 0.8990499455430013, "f1_weighted": 0.9037781287293268, "precision": 0.9000868799049606, "recall": 0.8981986428902734 }
RUCAIBox/mvp
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k_proj", "q_proj", "v_proj" ]
416,979,821
9,622,368
12
1253.23
1517.83
{ "accuracy": 0.9001738855516914, "f1_macro": 0.8947585729186707, "f1_weighted": 0.9004436495537628, "precision": 0.8950337321530449, "recall": 0.8947506574813173 }
RUCAIBox/mvp
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc2", "q_proj", "out_proj", "fc1", "dense", "v_proj", "k_proj" ]
424,553,031
17,195,578
12
1812.99
2335.75
{ "accuracy": 0.9046000632311098, "f1_macro": 0.900530338728399, "f1_weighted": 0.9047402806873164, "precision": 0.9017915749780111, "recall": 0.8995278468551758 }
answerdotai/ModernBERT-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "Wi", "Wo", "classifier", "dense" ]
403,417,831
7,573,210
12
1216.91
1257.05
{ "accuracy": 0.9046000632311098, "f1_macro": 0.9007031388663531, "f1_weighted": 0.904742331193519, "precision": 0.9021405291967194, "recall": 0.8994897048752831 }
answerdotai/ModernBERT-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "Wqkv" ]
398,339,309
2,494,688
12
895.53
767.32
{ "accuracy": 0.8964590578564654, "f1_macro": 0.8907832430093161, "f1_weighted": 0.896610379390417, "precision": 0.8916494643109869, "recall": 0.8901449731939147 }
answerdotai/ModernBERT-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "Wi", "classifier", "dense", "Wqkv", "Wo" ]
405,912,519
10,067,898
12
1408.45
1505.47
{ "accuracy": 0.902782168827063, "f1_macro": 0.8982363384586131, "f1_weighted": 0.9029750920279196, "precision": 0.89952706139945, "recall": 0.8972553397465217 }
facebook/bart-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "dense", "fc1", "fc2", "out_proj" ]
414,928,615
7,573,210
12
1130.3
1298.49
{ "accuracy": 0.9020708188428707, "f1_macro": 0.8976529273050624, "f1_weighted": 0.9022413332996261, "precision": 0.8987963121133778, "recall": 0.8968395748598041 }
facebook/bart-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k_proj", "q_proj", "v_proj" ]
416,977,773
9,622,368
12
1224.5
1433.39
{ "accuracy": 0.8979607967119823, "f1_macro": 0.893094704085986, "f1_weighted": 0.898250092183563, "precision": 0.8939508069907025, "recall": 0.8925932094406526 }
facebook/bart-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc2", "q_proj", "out_proj", "fc1", "dense", "v_proj", "k_proj" ]
424,550,983
17,195,578
12
1730.76
2232.1
{ "accuracy": 0.9043629465697123, "f1_macro": 0.9001995568888012, "f1_weighted": 0.904505371895914, "precision": 0.9017370599432847, "recall": 0.898953785314754 }
facebook/opt-125m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc1", "fc2", "out_proj", "score" ]
127,041,842
1,797,170
12
1024.46
512.82
{ "accuracy": 0.8882390135946886, "f1_macro": 0.8839564272236344, "f1_weighted": 0.8884397585361299, "precision": 0.8852831090129164, "recall": 0.8829656411891965 }
facebook/opt-125m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k_proj", "q_proj", "v_proj" ]
127,041,792
1,797,120
12
311.16
507.13
{ "accuracy": 0.8861049636421119, "f1_macro": 0.8807472864885908, "f1_weighted": 0.8861896488041808, "precision": 0.8815894239443753, "recall": 0.8801801964107973 }
facebook/opt-125m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc2", "q_proj", "out_proj", "fc1", "v_proj", "k_proj", "score" ]
128,838,962
3,594,290
12
441.58
829.68
{ "accuracy": 0.8902940246601327, "f1_macro": 0.8854706186724943, "f1_weighted": 0.8903978538018488, "precision": 0.8865887137966078, "recall": 0.8845377946533736 }
facebook/opt-350m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc1", "fc2", "out_proj", "project_in", "project_out", "score" ]
337,660,026
6,460,026
12
927.41
1016.09
{ "accuracy": 0.8946411634524186, "f1_macro": 0.8902380861526039, "f1_weighted": 0.8947638698016953, "precision": 0.8919213127206054, "recall": 0.8889995335197118 }
facebook/opt-350m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k_proj", "q_proj", "v_proj" ]
337,614,912
6,414,912
12
885.94
988.03
{ "accuracy": 0.8916376857413848, "f1_macro": 0.8865998406424822, "f1_weighted": 0.891787261637945, "precision": 0.8883432029350116, "recall": 0.8852117247775493 }
facebook/opt-350m
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "fc2", "q_proj", "out_proj", "fc1", "project_out", "project_in", "v_proj", "k_proj", "score" ]
344,074,938
12,874,938
12
1331.42
1657.95
{ "accuracy": 0.8933765412582991, "f1_macro": 0.8885361917141353, "f1_weighted": 0.8935432475545374, "precision": 0.8890092588928481, "recall": 0.8882755763620822 }
google-bert/bert-large-uncased
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "classifier", "dense" ]
341,659,271
6,504,058
12
857.3
1002.37
{ "accuracy": 0.8961429023079355, "f1_macro": 0.8918033143963418, "f1_weighted": 0.8962373050852591, "precision": 0.8924511812154367, "recall": 0.8912822386578682 }
google-bert/bert-large-uncased
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "key", "query", "value" ]
341,570,125
6,414,912
12
809.37
982.07
{ "accuracy": 0.8891874802402783, "f1_macro": 0.88337275072983, "f1_weighted": 0.8893712718064061, "precision": 0.8852227528843096, "recall": 0.8818844857698702 }
google-bert/bert-large-uncased
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "value", "classifier", "dense", "key", "query" ]
348,074,183
12,918,970
12
1251.84
1654.62
{ "accuracy": 0.894878280113816, "f1_macro": 0.8899907631419163, "f1_weighted": 0.8950773604328861, "precision": 0.890821415703024, "recall": 0.889419263453517 }
google-t5/t5-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "dense", "out_proj" ]
738,792,519
89,146
12
193.04
605.52
{ "accuracy": 0.7984508378122036, "f1_macro": 0.7830798444873828, "f1_weighted": 0.7979330162455205, "precision": 0.7906226981904548, "recall": 0.7783233213774022 }
google-t5/t5-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "k", "o", "q", "v", "wi", "wo" ]
772,916,237
34,212,864
12
3630.8
4878.33
{ "accuracy": 0.9032564021498577, "f1_macro": 0.897457529410699, "f1_weighted": 0.9034818956183636, "precision": 0.8982339150138509, "recall": 0.8969628578062715 }
google-t5/t5-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 200, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407,...
[ "wo", "out_proj", "q", "wi", "dense", "k", "v", "o" ]
773,005,383
34,302,010
12
3631.35
4898.05
{ "accuracy": 0.907682579829276, "f1_macro": 0.9026615393119441, "f1_weighted": 0.9078778438307681, "precision": 0.9034021521948665, "recall": 0.9021350606889726 }
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