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train · 16 rows

Model_name string	Train_size int64	Test_size int64	arg dict	lora null	Parameters int64	Trainable_parameters int64	r null	Memory Allocation string	Training Time string	Performance dict
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	407,356,429	407,356,429	null	5867.61	970.13	{ "accuracy": 0.8979607967119823, "f1_macro": 0.891852729470929, "f1_weighted": 0.8982383355393834, "precision": 0.8894310753123083, "recall": 0.8948273735707006 }
google/rembert	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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	575,935,373	575,935,373	null	7913.5	1270.83	{ "accuracy": 0.8958267467594057, "f1_macro": 0.8911675923140521, "f1_weighted": 0.8961273298975696, "precision": 0.8890851782500935, "recall": 0.8938949388413723 }
microsoft/deberta-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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	406,225,933	406,225,933	null	6266.85	1128.28	{ "accuracy": 0.8951153967752135, "f1_macro": 0.8893616798907913, "f1_weighted": 0.8954878749347206, "precision": 0.8875622216627826, "recall": 0.8918189939299015 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	355,373,069	355,373,069	null	4947.09	791.12	{ "accuracy": 0.8950363578880809, "f1_macro": 0.8894135449120755, "f1_weighted": 0.8954610792437828, "precision": 0.8867995536067526, "recall": 0.8929367204533054 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	559,903,757	559,903,757	null	7756.67	908.86	{ "accuracy": 0.8901359468858678, "f1_macro": 0.8850633445819885, "f1_weighted": 0.8905111778131922, "precision": 0.8822755904159911, "recall": 0.8887266147403385 }
albert/albert-xxlarge-v2	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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	222,648,845	222,648,845	null	5953.94	4896.57	{ "accuracy": 0.8327537148276952, "f1_macro": 0.82862046487544, "f1_weighted": 0.8357187003427415, "precision": 0.8322754407327498, "recall": 0.8325378956181434 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	595,789,824	595,789,824	null	8718.74	1339.56	{ "accuracy": 0.889661713563073, "f1_macro": 0.8846119518071507, "f1_weighted": 0.8898864092806986, "precision": 0.8834036869160283, "recall": 0.8861378564366966 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	407,354,381	407,354,381	null	5745.34	947.91	{ "accuracy": 0.8970913689535251, "f1_macro": 0.8908288766490828, "f1_weighted": 0.8974104104306859, "precision": 0.8883628990883273, "recall": 0.8941746430868415 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	331,203,072	331,203,072	null	4564.99	753.83	{ "accuracy": 0.8864211191906418, "f1_macro": 0.8802290649921711, "f1_weighted": 0.8866797518749822, "precision": 0.878929977272817, "recall": 0.8819710224231554 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	738,731,021	738,731,021	null	10939.35	1899.81	{ "accuracy": 0.8996996522288966, "f1_macro": 0.8936288908833862, "f1_weighted": 0.9001245194003096, "precision": 0.8909689984534453, "recall": 0.8971571108376603 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	335,155,213	335,155,213	null	7525.46	778.42	{ "accuracy": 0.8921119190641795, "f1_macro": 0.8865772241801698, "f1_weighted": 0.892484971245619, "precision": 0.884939797307305, "recall": 0.8891118248358614 }
FacebookAI/roberta-base	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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	124,655,629	124,655,629	null	3503.72	274.66	{ "accuracy": 0.8876857413847613, "f1_macro": 0.8814509616398547, "f1_weighted": 0.8881283392325012, "precision": 0.8787844637737946, "recall": 0.8851657480414475 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	125,249,280	125,249,280	null	1775.5	279.33	{ "accuracy": 0.8867372747391716, "f1_macro": 0.880888583051269, "f1_weighted": 0.8870039307021956, "precision": 0.8790493680308111, "recall": 0.8831317379087158 }
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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	395,844,621	395,844,621	null	5604.52	930.05	{ "accuracy": 0.8989883022447044, "f1_macro": 0.8939999313442495, "f1_weighted": 0.8991877469753808, "precision": 0.8935745356778734, "recall": 0.8946535715185413 }
google-bert/bert-base-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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	109,492,237	109,492,237	null	4293.26	265.31	{ "accuracy": 0.8851564969965223, "f1_macro": 0.8803987957600936, "f1_weighted": 0.8853440783717403, "precision": 0.8787057333969712, "recall": 0.8824766924512062 }
google/flan-t5-base	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, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "...	null	223,504,141	223,504,141	null	3905.4	909.05	{ "accuracy": 0.8895826746759405, "f1_macro": 0.8838822442923611, "f1_weighted": 0.8899085366048386, "precision": 0.8803108131992207, "recall": 0.8883744056751148 }

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