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Model_name
stringclasses
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Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
2
9
Parameters
int64
125M
739M
Trainable_parameters
int64
125M
739M
r
int64
48
128
Memory Allocation
stringclasses
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Training Time
stringclasses
10 values
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "dense", "value", "out_proj", "key", "query" ]
355,374,093
355,374,093
128
7139.29
1723.77
{ "accuracy": 0.8919538412899146, "f1_macro": 0.8851944961181825, "f1_weighted": 0.8927743121931819, "precision": 0.881241947563601, "recall": 0.891472727247562 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "dense", "out_proj" ]
559,904,781
559,904,781
48
11216.43
2314.38
{ "accuracy": 0.0902624091052798, "f1_macro": 0.012736864411505563, "f1_weighted": 0.01494558086098732, "precision": 0.006943262238867677, "recall": 0.07692307692307693 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "down_proj", "gate_proj", "o_proj", "score", "up_proj" ]
595,790,848
595,790,848
96
11935.89
2968.27
{ "accuracy": 0.8898988302244705, "f1_macro": 0.8821318513946826, "f1_weighted": 0.8908800904804247, "precision": 0.8780616199331112, "recall": 0.889021763347918 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "fc1", "dense", "k_proj", "out_proj", "q_proj", "fc2", "v_proj" ]
407,357,453
407,357,453
128
8160.17
2105.44
{ "accuracy": 0.8955896300980082, "f1_macro": 0.8896990362310925, "f1_weighted": 0.8963107492266744, "precision": 0.8859019826134203, "recall": 0.8952386314412812 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "classifier", "Wqkv", "dense", "Wo", "Wi" ]
395,844,621
395,844,621
112
7923.93
2019.74
{ "accuracy": 0.8982769522605122, "f1_macro": 0.8919094328139991, "f1_weighted": 0.8990645316349732, "precision": 0.8880357411461071, "recall": 0.8979348798436727 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "v_proj", "fc2", "out_proj", "fc1", "dense", "q_proj", "k_proj" ]
407,355,405
407,355,405
128
8158.55
2083.25
{ "accuracy": 0.8961429023079355, "f1_macro": 0.8892452689649409, "f1_weighted": 0.8971450664155236, "precision": 0.8854706134386038, "recall": 0.8958359492169533 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "v_proj", "fc2", "out_proj", "score", "fc1", "q_proj", "k_proj" ]
125,244,672
125,244,672
128
4366.84
566.79
{ "accuracy": 0.8848403414479924, "f1_macro": 0.8778881114824516, "f1_weighted": 0.885934942771535, "precision": 0.8743155378165819, "recall": 0.8841838802616303 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "v_proj", "fc2", "out_proj", "score", "project_in", "fc1", "q_proj", "k_proj", "project_out" ]
331,200,000
331,200,000
128
6630.02
1690.58
{ "accuracy": 0.8894245969016756, "f1_macro": 0.8827402403931696, "f1_weighted": 0.8901660888626195, "precision": 0.8795137850736006, "recall": 0.8876463670745974 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warm...
[ "classifier", "dense" ]
335,155,213
335,155,213
128
6715.26
1712.23
{ "accuracy": 0.8915586468542523, "f1_macro": 0.8852632041138917, "f1_weighted": 0.8923969817487253, "precision": 0.8820165311538072, "recall": 0.8904680288905091 }
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,...
[ "wi", "out_proj", "dense", "o", "wo", "v", "q", "k" ]
738,703,373
738,703,373
128
10609.1
3864.96
{ "accuracy": 0.8995415744546317, "f1_macro": 0.8934161411599081, "f1_weighted": 0.9001644075417934, "precision": 0.8897041123756932, "recall": 0.8985138739058842 }
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