Datasets:
ainewtrend07
/
EncoderLora

Dataset card Data Studio Files
xet
 Community
Model_name
string
Train_size
int64
Test_size
int64
arg
dict
lora
list
Parameters
int64
Trainable_parameters
int64
r
float64
Memory Allocation
string
Training Time
string
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", "key", "out_proj", "query", "value" ]
146,489,882
21,834,253
128
1589.37
754.82
{ "accuracy": 0.8785962693645274, "f1_macro": 0.8710648356088219, "f1_weighted": 0.8787506460209927, "precision": 0.8728281787608814, "recall": 0.8695968615798724 }
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 }
null
124,655,629
124,655,629
null
1367.8
334.5
{ "accuracy": 0.8925071134998419, "f1_macro": 0.887051396270736, "f1_weighted": 0.8926719997233882, "precision": 0.8882817518789956, "recall": 0.886081209807585 }
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 }
null
109,492,237
109,492,237
null
1168.05
322.07
{ "accuracy": 0.8932184634840341, "f1_macro": 0.8898298916067413, "f1_weighted": 0.893362825142097, "precision": 0.8908514366935851, "recall": 0.889085843429429 }
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", "key", "query", "value" ]
661,360,154
85,424,781
128
6548.37
3481.97
{ "accuracy": 0.9015965855200759, "f1_macro": 0.8970336687853184, "f1_weighted": 0.9018458022216244, "precision": 0.8982304900194211, "recall": 0.8961272149557615 }
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 }
null
575,935,373
575,935,373
null
3954.98
2053.34
{ "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": "adamw_8bit", "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
5936.7
1135.69
{ "accuracy": 0.896063863420803, "f1_macro": 0.892349299768241, "f1_weighted": 0.8962366922964575, "precision": 0.8934342673428037, "recall": 0.8916369554577288 }
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 }
null
355,373,069
355,373,069
null
3317.19
1023.67
{ "accuracy": 0.9008061966487512, "f1_macro": 0.8971203992512206, "f1_weighted": 0.9011314830951253, "precision": 0.8981519113849511, "recall": 0.8965336042335856 }
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", "key", "out_proj", "query", "value" ]
617,589,786
57,686,029
128
5755.54
2654.24
{ "accuracy": 0.8957477078722732, "f1_macro": 0.8908336420875144, "f1_weighted": 0.89600323293089, "precision": 0.8924190564442018, "recall": 0.8895911073887512 }
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 }
null
335,155,213
335,155,213
null
3077.82
1011.37
{ "accuracy": 0.8990673411318368, "f1_macro": 0.8946369857855598, "f1_weighted": 0.8992238587817474, "precision": 0.8955850125743764, "recall": 0.8939554389915754 }
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", "key", "out_proj", "query", "value" ]
413,059,098
57,686,029
128
4120.24
2179.47
{ "accuracy": 0.8955896300980082, "f1_macro": 0.8910125634203152, "f1_weighted": 0.8957623454439088, "precision": 0.891111273906099, "recall": 0.8910708781970247 }
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 }
null
395,844,621
395,844,621
null
3833.62
1126.04
{ "accuracy": 0.9059437243123617, "f1_macro": 0.9014572154672708, "f1_weighted": 0.9060630991030133, "precision": 0.9017012918476794, "recall": 0.9013572302614554 }
andreasmadsen/efficient_mlm_m0.40
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 }
null
355,375,117
355,375,117
null
3438.78
1033.7
{ "accuracy": 0.8799399304457793, "f1_macro": 0.8738139382198674, "f1_weighted": 0.8800773125733364, "precision": 0.8747373502244907, "recall": 0.8730621246492879 }
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 }
[ "Wi", "Wo", "Wqkv", "classifier", "dense" ]
453,693,466
57,848,845
128
2708.78
1417.26
{ "accuracy": 0.8862630414163769, "f1_macro": 0.8792670695586703, "f1_weighted": 0.8862810940200992, "precision": 0.881846847209354, "recall": 0.8771591947614554 }
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 }
null
406,225,933
406,225,933
null
4607.25
1387.8
{ "accuracy": 0.9013594688586785, "f1_macro": 0.8975140096191002, "f1_weighted": 0.9015398559268548, "precision": 0.897555513338138, "recall": 0.8977415330441111 }
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 }
[ "Wi", "Wo", "Wqkv", "classifier", "dense" ]
453,693,466
57,848,845
128
2692.36
1403.77
{ "accuracy": 0.8862630414163769, "f1_macro": 0.8792670695586703, "f1_weighted": 0.8862810940200992, "precision": 0.881846847209354, "recall": 0.8771591947614554 }
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", "pos_q_proj" ]
469,415,962
63,190,029
128
4538.33
2487.22
{ "accuracy": 0.8955896300980082, "f1_macro": 0.8898714302351564, "f1_weighted": 0.8959279312057375, "precision": 0.8895598897111395, "recall": 0.8904743418967348 }
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 }
null
222,648,845
222,648,845
null
5295.59
5875.08
{ "accuracy": 0.9015175466329434, "f1_macro": 0.8971965641975572, "f1_weighted": 0.9017035638945342, "precision": 0.8980348793252306, "recall": 0.8966264363248917 }
microsoft/deberta-v2-xlarge
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 }
null
886,973,965
886,973,965
null
10678.61
2741.26
{ "accuracy": 0.09318684792918115, "f1_macro": 0.013114352930707496, "f1_weighted": 0.015887107759164857, "precision": 0.007168219071475473, "recall": 0.07692307692307693 }
microsoft/deberta-v2-xlarge
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", "key_proj", "query_proj", "value_proj" ]
972,321,818
85,347,853
128
8858.14
16471.64
{ "accuracy": 0.9109231742017072, "f1_macro": 0.906644310826392, "f1_weighted": 0.9111162659647316, "precision": 0.907187848457159, "recall": 0.90632621594491 }