Model_name
stringlengths 12
33
| Train_size
int64 29.2k
50.8k
| Test_size
int64 7.3k
12.7k
| arg
dict | lora
null | Parameters
int64 109M
739M
| Trainable_parameters
int64 109M
739M
| r
null | Memory Allocation
stringlengths 6
8
| Training Time
stringlengths 6
8
| Performance
dict |
|---|---|---|---|---|---|---|---|---|---|---|
google-t5/t5-large
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 738,731,021
| 738,731,021
| null |
11588.28
|
2439.83
|
{
"accuracy": 0.905311413215302,
"f1_macro": 0.9001468326592003,
"f1_weighted": 0.9055258977504169,
"precision": 0.8997647095491552,
"recall": 0.9007592062400178
}
|
RUCAIBox/mvp
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,356,429
| 407,356,429
| null |
7237.18
|
1238.27
|
{
"accuracy": 0.9037306354726525,
"f1_macro": 0.899790061152644,
"f1_weighted": 0.9039185916524872,
"precision": 0.9003406292718075,
"recall": 0.899475423533622
}
|
facebook/bart-large-mnli
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,354,381
| 407,354,381
| null |
5912.1
|
1178.58
|
{
"accuracy": 0.9046791021182422,
"f1_macro": 0.9004031523813835,
"f1_weighted": 0.9049364768829319,
"precision": 0.9012616066439333,
"recall": 0.899805643350522
}
|
google/flan-t5-base
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 223,504,141
| 223,504,141
| null |
4195.79
|
860.96
|
{
"accuracy": 0.8925861523869744,
"f1_macro": 0.887617919892038,
"f1_weighted": 0.8926227324933397,
"precision": 0.8889503598540187,
"recall": 0.8864927381658047
}
|
facebook/bart-large
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,354,381
| 407,354,381
| null |
5962.44
|
1233.77
|
{
"accuracy": 0.902466013278533,
"f1_macro": 0.8980103056409068,
"f1_weighted": 0.9026728656106815,
"precision": 0.8987274426864164,
"recall": 0.8974978119714402
}
|
FacebookAI/roberta-base
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 130,320,852
| 130,320,852
| null |
2905.07
|
554.08
|
{
"accuracy": 0.27463341099081817,
"f1_macro": 0.00718026358955698,
"f1_weighted": 0.1592110676755744,
"precision": 0.006277277125165272,
"recall": 0.012833144249407423
}
|
google-bert/bert-base-uncased
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 115,157,460
| 115,157,460
| null |
2710.9
|
552.55
|
{
"accuracy": 0.25339180485130874,
"f1_macro": 0.005499402516701471,
"f1_weighted": 0.1358793175501451,
"precision": 0.0043077087743916805,
"recall": 0.010308437603367747
}
|
google/rembert
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 584,429,524
| 584,429,524
| null |
10879.12
|
3238.83
|
{
"accuracy": 0.038234891051116895,
"f1_macro": 0.0000316926175057751,
"f1_weighted": 0.0028161390188124642,
"precision": 0.000016452190641616565,
"recall": 0.0004302925989672978
}
|
FacebookAI/xlm-roberta-large
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 567,454,932
| 567,454,932
| null |
10221.62
|
1798.96
|
{
"accuracy": 0.038234891051116895,
"f1_macro": 0.0000316926175057751,
"f1_weighted": 0.0028161390188124642,
"precision": 0.000016452190641616565,
"recall": 0.0004302925989672978
}
|
FacebookAI/roberta-large
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 362,924,244
| 362,924,244
| null |
7767.25
|
1723.85
|
{
"accuracy": 0.038234891051116895,
"f1_macro": 0.0000316926175057751,
"f1_weighted": 0.0028161390188124642,
"precision": 0.000016452190641616565,
"recall": 0.0004302925989672978
}
|
google-bert/bert-large-uncased
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 342,706,388
| 342,706,388
| null |
7524.62
|
1714.2
|
{
"accuracy": 0.038234891051116895,
"f1_macro": 0.0000316926175057751,
"f1_weighted": 0.0028161390188124642,
"precision": 0.000016452190641616565,
"recall": 0.0004302925989672978
}
|
answerdotai/ModernBERT-large
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 403,395,796
| 403,395,796
| null |
9115.1
|
2085.41
|
{
"accuracy": 0.3449362751815815,
"f1_macro": 0.028710685639799498,
"f1_weighted": 0.2507159501037141,
"precision": 0.02645903933690301,
"recall": 0.0403564472558043
}
|
andreasmadsen/efficient_mlm_m0.40
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 362,926,292
| 362,926,292
| null |
9582.38
|
1914.38
|
{
"accuracy": 0.16157324928052624,
"f1_macro": 0.0011550620290914865,
"f1_weighted": 0.05812715037449428,
"precision": 0.000746305867522758,
"recall": 0.0032914033832205157
}
|
microsoft/deberta-large
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 413,777,108
| 413,777,108
| null |
15581.85
|
2726.35
|
{
"accuracy": 0.31848704947238593,
"f1_macro": 0.014595017171986416,
"f1_weighted": 0.2074780060789023,
"precision": 0.012767861825038196,
"recall": 0.02299426309908977
}
|
albert/albert-xxlarge-v2
| 29,188
| 7,297
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 252,831,444
| 252,831,444
| null |
14857.67
|
11517.15
|
{
"accuracy": 0.038234891051116895,
"f1_macro": 0.0000316926175057751,
"f1_weighted": 0.0028161390188124642,
"precision": 0.000016452190641616565,
"recall": 0.0004302925989672978
}
|
google/rembert
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 575,935,373
| 575,935,373
| null |
11362.96
|
10058.6
|
{
"accuracy": 0.09318684792918115,
"f1_macro": 0.013114352930707496,
"f1_weighted": 0.015887107759164857,
"precision": 0.007168219071475473,
"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": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 559,903,757
| 559,903,757
| null |
11211.07
|
2550.65
|
{
"accuracy": 0.9000158077774265,
"f1_macro": 0.896197393181218,
"f1_weighted": 0.900237657943695,
"precision": 0.8963125289239188,
"recall": 0.8963717186390119
}
|
FacebookAI/roberta-large
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 355,373,069
| 355,373,069
| null |
7111.97
|
1999.2
|
{
"accuracy": 0.9019917799557382,
"f1_macro": 0.89725405712224,
"f1_weighted": 0.9021952524586633,
"precision": 0.8965347970789997,
"recall": 0.8982035133570594
}
|
google-t5/t5-large
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 738,731,021
| 738,731,021
| null |
11588.28
|
1457.28
|
{
"accuracy": 0.9067341131836864,
"f1_macro": 0.9025164126614181,
"f1_weighted": 0.9069888812345382,
"precision": 0.9028649731936694,
"recall": 0.9024028117037944
}
|
RUCAIBox/mvp
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,356,429
| 407,356,429
| null |
7237.18
|
716.61
|
{
"accuracy": 0.90396775213405,
"f1_macro": 0.8996796299968829,
"f1_weighted": 0.9041053411616709,
"precision": 0.9004481467577173,
"recall": 0.8991369747406807
}
|
facebook/bart-large-mnli
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,354,381
| 407,354,381
| null |
5912.1
|
680.05
|
{
"accuracy": 0.9038887132469174,
"f1_macro": 0.8998128452032848,
"f1_weighted": 0.9040955792448577,
"precision": 0.9002449896492293,
"recall": 0.899607741675713
}
|
google/flan-t5-base
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 223,504,141
| 223,504,141
| null |
4195.79
|
819.97
|
{
"accuracy": 0.8934555801454316,
"f1_macro": 0.8880342734971147,
"f1_weighted": 0.8935988926251112,
"precision": 0.8893522316201353,
"recall": 0.8869647498717939
}
|
facebook/bart-large
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 407,354,381
| 407,354,381
| null |
5962.44
|
686.96
|
{
"accuracy": 0.9050742965539045,
"f1_macro": 0.900769902933932,
"f1_weighted": 0.9053382498008268,
"precision": 0.9016571663204758,
"recall": 0.9001964470074018
}
|
FacebookAI/roberta-base
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 124,655,629
| 124,655,629
| null |
4385.56
|
218.19
|
{
"accuracy": 0.8899778691116029,
"f1_macro": 0.8848329905104584,
"f1_weighted": 0.8900907430957858,
"precision": 0.885767288692668,
"recall": 0.8841083671451428
}
|
google-bert/bert-base-uncased
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
"weight_decay": 0.01
}
| null | 109,492,237
| 109,492,237
| null |
1688.47
|
216.14
|
{
"accuracy": 0.8926651912741068,
"f1_macro": 0.8886169207424561,
"f1_weighted": 0.8928197492691522,
"precision": 0.889444807314294,
"recall": 0.8880678792599225
}
|
google/rembert
| 50,775
| 12,652
|
{
"auto_find_batch_size": true,
"gradient_accumulation_steps": 4,
"learning_rate": 0.00005,
"logging_steps": 1,
"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,
"warmup_steps": 5,
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FacebookAI/xlm-roberta-large
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| null | 559,903,757
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FacebookAI/roberta-large
| 50,775
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{
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| null | 355,373,069
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albert/albert-xxlarge-v2
| 50,775
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| null | 222,648,845
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google-bert/bert-large-uncased
| 50,775
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{
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| null | 335,155,213
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answerdotai/ModernBERT-large
| 50,775
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| null | 395,844,621
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microsoft/deberta-large
| 50,775
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| null | 406,225,933
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6680.97
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|
albert/albert-xxlarge-v2
| 50,775
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| null | 222,648,845
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6600.11
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|
Qwen/Qwen3-Reranker-0.6B
| 50,775
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{
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| null | 595,789,824
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|
facebook/opt-350m
| 50,775
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| null | 331,203,072
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|
facebook/opt-125m
| 50,775
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{
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| null | 125,249,280
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2019.24
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564.28
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|
Qwen/Qwen3-Reranker-0.6B
| 50,775
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{
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| null | 595,789,824
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6563.3
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|
facebook/opt-350m
| 50,775
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{
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| null | 331,203,072
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2907.05
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|
facebook/opt-125m
| 50,775
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{
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| null | 125,249,280
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1539.88
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