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ainewtrend07
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HyperLora

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Model_name
stringclasses
16 values
Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
1
9
Parameters
int64
110M
1.85B
Trainable_parameters
int64
9.27k
1.11B
r
int64
4
1.02k
Memory Allocation
stringlengths
5
7
Training Time
stringlengths
5
7
Performance
dict
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
125,698,586
1,042,957
4
1379.61
516.83
{ "accuracy": 0.8465855200758773, "f1_macro": 0.8340490920495849, "f1_weighted": 0.8465504941446558, "precision": 0.8402862114476798, "recall": 0.8301870667970347 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
126,140,954
1,485,325
8
1375.29
539.19
{ "accuracy": 0.8593898197913373, "f1_macro": 0.8494724159910976, "f1_weighted": 0.8595404905204881, "precision": 0.8537412420731172, "recall": 0.8464116130684702 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
127,025,690
2,370,061
16
1379.01
524.26
{ "accuracy": 0.8689535251343661, "f1_macro": 0.860226577406406, "f1_weighted": 0.8691191048708272, "precision": 0.8630581563058186, "recall": 0.8579840198270493 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
128,795,162
4,139,533
32
1405.63
522.2
{ "accuracy": 0.873300663926652, "f1_macro": 0.8652518906400283, "f1_weighted": 0.8734504853470856, "precision": 0.8671457037466545, "recall": 0.8637183716416306 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
132,334,106
7,678,477
64
1470.14
538.22
{ "accuracy": 0.879544736010117, "f1_macro": 0.8717421988175561, "f1_weighted": 0.8796959266260036, "precision": 0.8729376208017359, "recall": 0.8708070546286392 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
139,411,994
14,756,365
128
1474.88
564.83
{ "accuracy": 0.8837337970281378, "f1_macro": 0.8764199863238034, "f1_weighted": 0.8838460171049024, "precision": 0.8775010379877884, "recall": 0.8755335295237698 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
408,644,673
1,290,292
4
3792.74
1765.12
{ "accuracy": 0.8254030983243756, "f1_macro": 0.7942233737452272, "f1_weighted": 0.8210719850322569, "precision": 0.8155352712384848, "recall": 0.7892248972999769 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
357,615,642
2,242,573
4
3299.3
1456.24
{ "accuracy": 0.8762251027505533, "f1_macro": 0.8692030515942923, "f1_weighted": 0.8765679781573217, "precision": 0.8711681710386169, "recall": 0.8678851272646673 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
153,567,770
28,912,141
256
1649.39
622.11
{ "accuracy": 0.8876857413847613, "f1_macro": 0.8811070927831653, "f1_weighted": 0.8877647364230433, "precision": 0.8822983580334766, "recall": 0.8800895685744806 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
562,146,330
2,242,573
4
4935.54
2021.03
{ "accuracy": 0.8725893139424596, "f1_macro": 0.8648132854936866, "f1_weighted": 0.8727950240317498, "precision": 0.867549548960421, "recall": 0.8626542247550917 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
109,950,746
458,509
4
1248.45
503.85
{ "accuracy": 0.6804457793234271, "f1_macro": 0.5831976548071854, "f1_weighted": 0.6489669753037608, "precision": 0.6552885170242525, "recall": 0.6076809656621555 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
577,734,682
1,799,309
4
5007.36
2625.72
{ "accuracy": 0.8695858362314258, "f1_macro": 0.8589912882110775, "f1_weighted": 0.8695841347189455, "precision": 0.8637437350730561, "recall": 0.855559709905021 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
110,399,258
907,021
8
1244.82
501.33
{ "accuracy": 0.7468384445147013, "f1_macro": 0.6780446340268369, "f1_weighted": 0.7257716525873043, "precision": 0.698242661197289, "recall": 0.6866301155276309 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
181,879,322
57,223,693
512
1948.99
745.42
{ "accuracy": 0.89084729687006, "f1_macro": 0.884702784129353, "f1_weighted": 0.8909290679599178, "precision": 0.8857158320594325, "recall": 0.883844733737056 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
358,795,290
3,422,221
8
3308.5
1466.79
{ "accuracy": 0.8821530192854885, "f1_macro": 0.8763401875319281, "f1_weighted": 0.8825445854181906, "precision": 0.877769674405757, "recall": 0.8753882277725543 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
111,296,282
1,804,045
16
1248.79
479.4
{ "accuracy": 0.7977394878280114, "f1_macro": 0.7523181078518651, "f1_weighted": 0.7862311782799655, "precision": 0.7982886603247584, "recall": 0.7532144822533675 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
409,934,965
2,580,584
8
3804.75
1765.81
{ "accuracy": 0.8494309200126462, "f1_macro": 0.8324264851760286, "f1_weighted": 0.8484212760977864, "precision": 0.8410424107713527, "recall": 0.8278077509740616 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
113,090,330
3,598,093
32
1274.29
503.21
{ "accuracy": 0.8400252924438824, "f1_macro": 0.8241649565993185, "f1_weighted": 0.838801434313264, "precision": 0.837904148263822, "recall": 0.8168347742360932 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
563,325,978
3,422,221
8
4944.75
2016.25
{ "accuracy": 0.8814416693012962, "f1_macro": 0.8750724802105493, "f1_weighted": 0.8815682095432281, "precision": 0.8771349816062244, "recall": 0.8733434004724216 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
116,678,426
7,186,189
64
1341.59
523.13
{ "accuracy": 0.856307303193171, "f1_macro": 0.8445821685599258, "f1_weighted": 0.8558074261383034, "precision": 0.8532108533533793, "recall": 0.8394980941298701 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
361,154,586
5,781,517
16
3335.47
1467.59
{ "accuracy": 0.8860259247549794, "f1_macro": 0.8805908113119117, "f1_weighted": 0.8862769058797022, "precision": 0.8815056148370751, "recall": 0.8799666252638331 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
123,854,618
14,362,381
128
1348.89
550.71
{ "accuracy": 0.8682421751501739, "f1_macro": 0.8607836525623542, "f1_weighted": 0.8681785403418177, "precision": 0.8650231484647595, "recall": 0.8575399385906514 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
412,515,549
5,161,168
16
3836.41
1775.46
{ "accuracy": 0.8675308251659817, "f1_macro": 0.8569831684700908, "f1_weighted": 0.8675100017298956, "precision": 0.8611393290578584, "recall": 0.8542100346505586 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
579,519,002
3,583,629
8
5026.7
2631.96
{ "accuracy": 0.8827853303825483, "f1_macro": 0.8758300378165708, "f1_weighted": 0.8829383871624759, "precision": 0.87862067881592, "recall": 0.8735385090229185 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
138,207,002
28,714,765
256
1518.54
612.14
{ "accuracy": 0.8768574138476131, "f1_macro": 0.8711695243461549, "f1_weighted": 0.8768884317753117, "precision": 0.8737841851778931, "recall": 0.8690053543037654 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
365,873,178
10,500,109
32
3414.77
1477.69
{ "accuracy": 0.8906892190957951, "f1_macro": 0.8860021264947283, "f1_weighted": 0.8909334482337231, "precision": 0.8868374971079175, "recall": 0.8854509207788522 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
125,477,402
821,773
4
1156.22
550.26
{ "accuracy": 0.8340183370218147, "f1_macro": 0.8198675525987951, "f1_weighted": 0.8337764478041396, "precision": 0.8259594334694711, "recall": 0.8159187392243591 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
166,911,770
57,419,533
512
1841.63
733.87
{ "accuracy": 0.882232058172621, "f1_macro": 0.8773384152398953, "f1_weighted": 0.8823046399232333, "precision": 0.8795561471893543, "recall": 0.8755108966229024 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
336,356,378
1,201,165
4
729.05
555.38
{ "accuracy": 0.815523237432817, "f1_macro": 0.7794404234917954, "f1_weighted": 0.8089604529608558, "precision": 0.8165454155559532, "recall": 0.7735023676594606 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
125,698,586
1,042,957
8
1150.03
536.72
{ "accuracy": 0.8510907366424281, "f1_macro": 0.8400420874226526, "f1_weighted": 0.8511327945816213, "precision": 0.8457216333479073, "recall": 0.8361739028568304 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
417,676,717
10,322,336
32
3916.76
1790.55
{ "accuracy": 0.8758299083148909, "f1_macro": 0.8668049587329789, "f1_weighted": 0.8758603217556982, "precision": 0.8697313514600873, "recall": 0.8646167954835591 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
337,544,218
2,389,005
8
719.58
554.83
{ "accuracy": 0.8619190641795763, "f1_macro": 0.8523901695902638, "f1_weighted": 0.862036251000165, "precision": 0.8565319337706493, "recall": 0.8494140859579764 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
126,140,954
1,485,325
16
1149.65
536.95
{ "accuracy": 0.8595478975656022, "f1_macro": 0.8495386110208438, "f1_weighted": 0.8596940655110615, "precision": 0.8539706656018181, "recall": 0.8463705209445991 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
375,310,362
19,937,293
64
3575.49
1522.37
{ "accuracy": 0.8940088523553589, "f1_macro": 0.8896207971222672, "f1_weighted": 0.8941604025617136, "precision": 0.8906132689531988, "recall": 0.8888308789628273 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
339,919,898
4,764,685
16
734.77
557.47
{ "accuracy": 0.8700600695542207, "f1_macro": 0.8629267469057272, "f1_weighted": 0.8703546878001558, "precision": 0.8662414806607376, "recall": 0.8604568138886367 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
109,944,602
452,365
8
1010.89
495.67
{ "accuracy": 0.5833069870376225, "f1_macro": 0.47480777422523524, "f1_weighted": 0.5335707257009746, "precision": 0.503493398959869, "recall": 0.5156260517847151 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
127,025,690
2,370,061
32
1175.96
538.72
{ "accuracy": 0.8669775529560544, "f1_macro": 0.8582782106285267, "f1_weighted": 0.8671392295134541, "precision": 0.8613026321631628, "recall": 0.8559757886864787 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
583,087,642
7,152,269
16
5074.65
2648.51
{ "accuracy": 0.89084729687006, "f1_macro": 0.8852825636698043, "f1_weighted": 0.8910752417418889, "precision": 0.887225855993687, "recall": 0.8836901840064006 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
570,403,866
10,500,109
32
5042.86
2045.0
{ "accuracy": 0.8910844135314575, "f1_macro": 0.8854909910992065, "f1_weighted": 0.8912291024968251, "precision": 0.887047946004157, "recall": 0.8841939914729813 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
110,386,970
894,733
16
1018.89
496.81
{ "accuracy": 0.6585520075877331, "f1_macro": 0.5583557193327258, "f1_weighted": 0.618386260774831, "precision": 0.625158519422246, "recall": 0.5892689860021918 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
128,795,162
4,139,533
64
1175.42
544.46
{ "accuracy": 0.8714037306354726, "f1_macro": 0.8629328315448218, "f1_weighted": 0.8714950054507163, "precision": 0.8654034306031588, "recall": 0.860973347921311 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
344,671,258
9,516,045
32
765.14
563.24
{ "accuracy": 0.8773316471704078, "f1_macro": 0.8708971632647742, "f1_weighted": 0.8775584683512808, "precision": 0.8730965955606386, "recall": 0.8692390386775077 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
111,271,706
1,779,469
32
1042.97
498.7
{ "accuracy": 0.7338760670249763, "f1_macro": 0.6800897675258101, "f1_weighted": 0.7154343448169183, "precision": 0.7471161150451973, "recall": 0.6864654554372182 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
132,334,106
7,678,477
128
1212.37
555.17
{ "accuracy": 0.8763831805248182, "f1_macro": 0.8685086985495007, "f1_weighted": 0.8764768753528103, "precision": 0.8706212561474461, "recall": 0.86678235158233 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
427,999,053
20,644,672
64
4107.01
1845.35
{ "accuracy": 0.8829434081568132, "f1_macro": 0.8760990330726381, "f1_weighted": 0.8830823425417631, "precision": 0.878388529941251, "recall": 0.874255558547274 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
354,173,978
19,018,765
64
825.99
584.63
{ "accuracy": 0.880730319317104, "f1_macro": 0.8745132364205285, "f1_weighted": 0.8808686332353639, "precision": 0.8761351934239846, "recall": 0.8732603833811635 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
113,041,178
3,548,941
64
1039.2
506.87
{ "accuracy": 0.7899936768890294, "f1_macro": 0.76085900959247, "f1_weighted": 0.7837586524219583, "precision": 0.7904333025476757, "recall": 0.7563708284429409 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
394,184,730
38,811,661
128
3649.15
1618.89
{ "accuracy": 0.89756560227632, "f1_macro": 0.8931155672712718, "f1_weighted": 0.8977212994148122, "precision": 0.8940294746357065, "recall": 0.8924113005747072 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
139,411,994
14,756,365
256
1347.02
589.18
{ "accuracy": 0.8800980082200442, "f1_macro": 0.8728568319907553, "f1_weighted": 0.8802014973485958, "precision": 0.8744470212702262, "recall": 0.8716389976774788 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
373,179,418
38,024,205
128
950.71
618.54
{ "accuracy": 0.8842080303509326, "f1_macro": 0.8784351126961792, "f1_weighted": 0.884335007759456, "precision": 0.8796394785271359, "recall": 0.8775049888168863 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
116,580,122
7,087,885
128
1079.39
499.2
{ "accuracy": 0.8262725260828327, "f1_macro": 0.8044735145506146, "f1_weighted": 0.8236107619440158, "precision": 0.8181056541984145, "recall": 0.7992784227671461 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
153,567,770
28,912,141
512
1549.04
642.82
{ "accuracy": 0.8823110970597534, "f1_macro": 0.8752709699074926, "f1_weighted": 0.8824236522894506, "precision": 0.8759907367639677, "recall": 0.8747700003957696 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
579,841,050
19,937,293
64
5211.23
2092.91
{ "accuracy": 0.8938507745810939, "f1_macro": 0.8889839784997207, "f1_weighted": 0.8939976610165367, "precision": 0.8907862703375223, "recall": 0.8874784323164315 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
123,658,010
14,165,773
256
1214.8
539.47
{ "accuracy": 0.8452418589946253, "f1_macro": 0.8309024960657764, "f1_weighted": 0.8445499077974197, "precision": 0.8380230325734844, "recall": 0.8264247931667552 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
411,190,298
76,035,085
256
1209.98
696.93
{ "accuracy": 0.8861840025292443, "f1_macro": 0.8805852219073909, "f1_weighted": 0.8862916923417463, "precision": 0.8815998520714247, "recall": 0.8798811297517187 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
590,224,922
14,289,549
32
5184.43
2675.98
{ "accuracy": 0.8965380967435979, "f1_macro": 0.8916888027728069, "f1_weighted": 0.8967334029305609, "precision": 0.8939975604190971, "recall": 0.8897654555741151 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
448,643,725
41,289,344
128
4188.89
1954.45
{ "accuracy": 0.8895036357888081, "f1_macro": 0.8833073806422669, "f1_weighted": 0.8896636096198612, "precision": 0.884459853381671, "recall": 0.8823866083639367 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
137,813,786
28,321,549
512
1426.05
605.12
{ "accuracy": 0.85883654758141, "f1_macro": 0.848513365806343, "f1_weighted": 0.8586877233616093, "precision": 0.8537204028707317, "recall": 0.8448018864192982 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
431,933,466
76,560,397
256
4148.11
1794.14
{ "accuracy": 0.8996206133417641, "f1_macro": 0.8952887187406523, "f1_weighted": 0.8997428572588272, "precision": 0.8962920572695677, "recall": 0.894464186628896 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense" ]
487,212,058
152,056,845
512
1703.09
864.14
{ "accuracy": 0.8863420803035094, "f1_macro": 0.8809090607240366, "f1_weighted": 0.8864747176495101, "precision": 0.8811480559502635, "recall": 0.8809128972730303 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
335,758,362
603,149
4
917.44
546.92
{ "accuracy": 0.887132469174834, "f1_macro": 0.8817187487987473, "f1_weighted": 0.8872365394026598, "precision": 0.8824020330476059, "recall": 0.8812280581703731 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
396,316,698
472,077
4
1834.11
786.35
{ "accuracy": 0.7903098324375593, "f1_macro": 0.7672491813607067, "f1_weighted": 0.7886414085185387, "precision": 0.7749200809729936, "recall": 0.7629213053908442 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
598,715,418
38,811,661
128
5282.39
2191.98
{ "accuracy": 0.896380018969333, "f1_macro": 0.8918873284178506, "f1_weighted": 0.8965179629653568, "precision": 0.8931920068877847, "recall": 0.8908658698341267 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
336,348,186
1,192,973
8
573.23
547.32
{ "accuracy": 0.8872905469490989, "f1_macro": 0.8820272426764626, "f1_weighted": 0.8873896526508074, "precision": 0.8828409744012747, "recall": 0.8813973789041893 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
396,775,450
930,829
8
1840.15
789.62
{ "accuracy": 0.8280904204868795, "f1_macro": 0.8127439252127046, "f1_weighted": 0.8277441204563218, "precision": 0.8170094648812616, "recall": 0.8095579199545097 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
337,527,834
2,372,621
16
581.2
548.24
{ "accuracy": 0.8875276636104964, "f1_macro": 0.8822620778352918, "f1_weighted": 0.8876157933246032, "precision": 0.8830131811926824, "recall": 0.881689667346855 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
489,933,069
82,578,688
256
4775.35
2149.02
{ "accuracy": 0.8957477078722732, "f1_macro": 0.8909291187592895, "f1_weighted": 0.8958900440066224, "precision": 0.8917778185527342, "recall": 0.8902739783190025 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
507,430,938
152,057,869
512
5208.02
2154.21
{ "accuracy": 0.9023869743914006, "f1_macro": 0.8975241027323866, "f1_weighted": 0.902511886689775, "precision": 0.8983383090095226, "recall": 0.8968883767529492 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
604,499,482
28,564,109
64
5410.55
2756.43
{ "accuracy": 0.8986721466961746, "f1_macro": 0.8942493548634695, "f1_weighted": 0.8988471414290032, "precision": 0.8961804074671618, "recall": 0.8926048577899264 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
339,887,130
4,731,917
32
597.12
551.81
{ "accuracy": 0.8875276636104964, "f1_macro": 0.8822690294260441, "f1_weighted": 0.8876324867403612, "precision": 0.8830941233036421, "recall": 0.8816375818813812 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
397,692,954
1,848,333
16
1854.29
814.45
{ "accuracy": 0.8442933923490358, "f1_macro": 0.8317764391177607, "f1_weighted": 0.8440530174431455, "precision": 0.835826797307839, "recall": 0.8286484142313467 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
344,605,722
9,450,509
64
629.12
559.8
{ "accuracy": 0.887132469174834, "f1_macro": 0.8818528902639416, "f1_weighted": 0.8872188116550366, "precision": 0.8824483754035293, "recall": 0.8814262519162981 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
399,527,962
3,683,341
32
1890.68
792.05
{ "accuracy": 0.8579671198229529, "f1_macro": 0.8475435628380684, "f1_weighted": 0.8578404191364576, "precision": 0.8507979439495266, "recall": 0.8449504002910871 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
636,464,154
76,560,397
256
5783.89
2368.27
{ "accuracy": 0.8991463800189693, "f1_macro": 0.8943440596520253, "f1_weighted": 0.8992907008437808, "precision": 0.8956325153176388, "recall": 0.8932812078131077 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
357,025,818
1,652,749
4
3283.36
1447.14
{ "accuracy": 0.866740436294657, "f1_macro": 0.8575637104818205, "f1_weighted": 0.8669708348834821, "precision": 0.8608586794600368, "recall": 0.8551682938094264 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
354,042,906
18,887,693
128
693.11
572.79
{ "accuracy": 0.8870534302877016, "f1_macro": 0.8818615284745714, "f1_weighted": 0.8871316748564163, "precision": 0.8823367797181898, "recall": 0.8815199668222549 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
372,917,274
37,762,061
256
821.11
609.05
{ "accuracy": 0.885946885867847, "f1_macro": 0.8812526997751445, "f1_weighted": 0.8859959148203225, "precision": 0.8816106503696065, "recall": 0.881007863260953 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
403,197,978
7,353,357
64
1944.59
803.9
{ "accuracy": 0.8696648751185583, "f1_macro": 0.8615520466335258, "f1_weighted": 0.8696118331637468, "precision": 0.8646678666301584, "recall": 0.8590107351236551 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "fc1", "fc2", "out_proj" ]
572,511,757
165,157,376
512
5814.55
2568.12
{ "accuracy": 0.8993044577932343, "f1_macro": 0.8948132965953287, "f1_weighted": 0.8994168863709725, "precision": 0.8956847616023478, "recall": 0.8941679009907664 }
microsoft/deberta-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "in_proj", "pos_proj" ]
408,016,922
1,790,989
4
3613.07
1898.71
{ "accuracy": 0.8578090420486879, "f1_macro": 0.8446092300628985, "f1_weighted": 0.8578612785245953, "precision": 0.8492567246489446, "recall": 0.8418384523871402 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
357,615,642
2,242,573
8
3292.14
1435.24
{ "accuracy": 0.8760670249762883, "f1_macro": 0.8692705789045871, "f1_weighted": 0.8764015848224459, "precision": 0.8713756336119993, "recall": 0.867732993727411 }
google-bert/bert-large-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
410,666,010
75,510,797
512
1114.18
683.0
{ "accuracy": 0.884603224786595, "f1_macro": 0.878605207347677, "f1_weighted": 0.8847180290634366, "precision": 0.8782405610261594, "recall": 0.8791753431973165 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
633,048,602
57,113,229
128
5810.97
2901.63
{ "accuracy": 0.9019917799557382, "f1_macro": 0.8982219370986022, "f1_weighted": 0.9021507602038787, "precision": 0.900625623362189, "recall": 0.8961772457902 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
410,538,010
14,693,389
128
2042.92
831.97
{ "accuracy": 0.874328169459374, "f1_macro": 0.8665932773699195, "f1_weighted": 0.8742417767025412, "precision": 0.8692475565339852, "recall": 0.8643949760993761 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "dense", "out_proj" ]
711,961,626
152,057,869
512
6843.98
2713.87
{ "accuracy": 0.9010433133101486, "f1_macro": 0.8969479131518704, "f1_weighted": 0.9012152952855088, "precision": 0.8976570979548679, "recall": 0.8964894216574089 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
425,218,074
29,373,453
256
2248.69
874.61
{ "accuracy": 0.8794656971229845, "f1_macro": 0.8726974236966247, "f1_weighted": 0.8794719106552626, "precision": 0.8747160009190501, "recall": 0.8710901196893861 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
358,795,290
3,422,221
16
3308.33
1440.69
{ "accuracy": 0.8818368637369586, "f1_macro": 0.875790887031754, "f1_weighted": 0.8821591776492361, "precision": 0.8772440147930095, "recall": 0.8747788935196866 }
microsoft/deberta-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "in_proj", "pos_proj" ]
409,794,586
3,568,653
8
3629.29
1895.48
{ "accuracy": 0.874328169459374, "f1_macro": 0.8641103102381869, "f1_weighted": 0.8745478117117244, "precision": 0.866397138011316, "recall": 0.8629314782882648 }
answerdotai/ModernBERT-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "Wqkv" ]
454,578,202
58,733,581
512
2562.46
944.06
{ "accuracy": 0.8840499525766677, "f1_macro": 0.8772364746801417, "f1_weighted": 0.8840641342001619, "precision": 0.8791632119549534, "recall": 0.8756725309481499 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "k_proj", "q_proj", "v_proj" ]
408,239,117
884,736
4
3882.55
1795.46
{ "accuracy": 0.25418906101802086, "f1_macro": 0.16746654763773686, "f1_weighted": 0.19839063988848946, "precision": 0.22534217234371567, "recall": 0.2100578649092377 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
361,154,586
5,781,517
32
3344.93
1466.0
{ "accuracy": 0.8857888080935821, "f1_macro": 0.8799275312566462, "f1_weighted": 0.886121637308196, "precision": 0.8808806803033844, "recall": 0.8793853471902271 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in" ]
690,146,842
114,211,469
256
6479.82
3174.09
{ "accuracy": 0.90396775213405, "f1_macro": 0.9000784127377291, "f1_weighted": 0.9041240754395038, "precision": 0.901687898049922, "recall": 0.8987227054048579 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
561,556,506
1,652,749
4
4920.26
1993.61
{ "accuracy": 0.861681947518179, "f1_macro": 0.8518543085684569, "f1_weighted": 0.8616834766914389, "precision": 0.8557438409368476, "recall": 0.8491147729646762 }
microsoft/deberta-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "in_proj", "pos_proj" ]
413,349,914
7,123,981
16
3671.11
1911.46
{ "accuracy": 0.8819949415112235, "f1_macro": 0.8740560385409323, "f1_weighted": 0.8822275343532041, "precision": 0.874914517996927, "recall": 0.8736064228611521 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
365,873,178
10,500,109
64
3416.66
1495.35
{ "accuracy": 0.8890294024660133, "f1_macro": 0.8832128667872327, "f1_weighted": 0.889326249515431, "precision": 0.8837432896318163, "recall": 0.8829964929542189 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "k_proj", "q_proj", "v_proj" ]
409,123,853
1,769,472
8
3896.36
1772.8
{ "accuracy": 0.6342870692380651, "f1_macro": 0.5243534507803612, "f1_weighted": 0.5969217399151321, "precision": 0.5656195963958232, "recall": 0.5562342366705734 }
albert/albert-xxlarge-v2
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "embedding_hidden_mapping_in", "ffn", "ffn_output", "pooler" ]
222,948,378
299,533
4
2293.62
3286.26
{ "accuracy": 0.7384603224786594, "f1_macro": 0.6632644496543156, "f1_weighted": 0.7188668278957628, "precision": 0.7557279016742403, "recall": 0.6736103242013692 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
562,146,330
2,242,573
8
4929.63
1982.89
{ "accuracy": 0.8754347138792286, "f1_macro": 0.8684851872815932, "f1_weighted": 0.8756161000577907, "precision": 0.8711312369445623, "recall": 0.8663700730948646 }
microsoft/deberta-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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "classifier", "dense", "in_proj", "pos_proj" ]
420,460,570
14,234,637
32
3773.31
1937.34
{ "accuracy": 0.8883970913689535, "f1_macro": 0.881447477588251, "f1_weighted": 0.8885959982355389, "precision": 0.8823729100014337, "recall": 0.8808481640861859 }
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": "adamw_8bit", "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
[ "key", "query", "value" ]
375,310,362
19,937,293
128
3589.87
1523.41
{ "accuracy": 0.8900569079987354, "f1_macro": 0.8840841051769437, "f1_weighted": 0.8903668026826507, "precision": 0.8849892661664793, "recall": 0.8835230328349574 }
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