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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
7139.27
1696.85
{ "accuracy": 0.047186215618084094, "f1_macro": 0.0069323083890221035, "f1_weighted": 0.0042524221788808525, "precision": 0.0036297088936987766, "recall": 0.07692307692307693 }
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
11216.38
2255.28
{ "accuracy": 0.8926651912741068, "f1_macro": 0.8873566241534654, "f1_weighted": 0.893021519400735, "precision": 0.8848556687214065, "recall": 0.8907650681408374 }
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
10250.24
1474.19
{ "accuracy": 0.8815997470755612, "f1_macro": 0.8756919344659947, "f1_weighted": 0.8821042167047373, "precision": 0.8722091956644628, "recall": 0.8804270641841092 }
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
8160.12
2019.55
{ "accuracy": 0.8982769522605122, "f1_macro": 0.8925015109426846, "f1_weighted": 0.8985326099916416, "precision": 0.8903778703786831, "recall": 0.8952461845578182 }
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
6457.03
1033.1
{ "accuracy": 0.8940088523553589, "f1_macro": 0.8886816529829437, "f1_weighted": 0.8942663169684953, "precision": 0.8870933408766797, "recall": 0.8907157018337559 }
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
8159.21
2018.87
{ "accuracy": 0.8988302244704395, "f1_macro": 0.8929750241639187, "f1_weighted": 0.899256559919618, "precision": 0.8908005189849331, "recall": 0.8960528781650959 }
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
549.37
{ "accuracy": 0.8872905469490989, "f1_macro": 0.8817126861110668, "f1_weighted": 0.8875715217045255, "precision": 0.8795867253259687, "recall": 0.8843829758646979 }
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
6629.97
1616.33
{ "accuracy": 0.8860259247549794, "f1_macro": 0.879883326176835, "f1_weighted": 0.8862515001809005, "precision": 0.8773090238722309, "recall": 0.8829976175059239 }
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
6713.17
1653.2
{ "accuracy": 0.888634208030351, "f1_macro": 0.8828912872539122, "f1_weighted": 0.8889276326842342, "precision": 0.8807236742151657, "recall": 0.8858827951760831 }
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
10609.05
3795.29
{ "accuracy": 0.8980398355991147, "f1_macro": 0.8924658106904624, "f1_weighted": 0.8985489279000564, "precision": 0.889984481475139, "recall": 0.8958798490124761 }
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