Hugging Face's logo

Datasets:
ainewtrend07
/
FullReport

Modalities:
Tabular
Text
Formats:
parquet
Size:
< 1K
Libraries:
Datasets
pandas
Dataset card Data Studio Files
xet
Community
1
Dataset Viewer
Auto-converted to Parquet Duplicate
Model_name
stringlengths
12
35
Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
3
9
⌀
Parameters
int64
125M
972M
Trainable_parameters
int64
94.3k
887M
r
float64
12
128
⌀
Memory Allocation
stringlengths
6
8
Training Time
stringlengths
6
8
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 }
null
124,656,398
124,656,398
null
1695.39
1099.62
{ "accuracy": 0.8932184634840341, "f1_macro": 0.8875093633292557, "f1_weighted": 0.8933848788288816, "precision": 0.8883486211079243, "recall": 0.8868750494021655 }
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
9707.34
5796.95
{ "accuracy": 0.09318684792918115, "f1_macro": 0.013114352930707496, "f1_weighted": 0.015887107759164857, "precision": 0.007168219071475473, "recall": 0.07692307692307693 }
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
1592.17
1030.47
{ "accuracy": 0.8798608915586469, "f1_macro": 0.8721820472848224, "f1_weighted": 0.8799427434857163, "precision": 0.8731432731323735, "recall": 0.8714329080438282 }
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
1890.36
606.48
{ "accuracy": 0.8915586468542523, "f1_macro": 0.8859316634255782, "f1_weighted": 0.8917288188081988, "precision": 0.8870564678615502, "recall": 0.8851432719254876 }
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
783.28
{ "accuracy": 0.8778849193803351, "f1_macro": 0.8698334558449677, "f1_weighted": 0.8781089024873767, "precision": 0.8718728217994387, "recall": 0.8681508641379924 }
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", "key", "query", "value" ]
130,932,506
21,440,269
128
1444.18
760.23
{ "accuracy": 0.8724312361681947, "f1_macro": 0.8647376392889488, "f1_weighted": 0.8725451868299441, "precision": 0.8662538417263007, "recall": 0.8635665331183634 }
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
11843.22
5144.4
{ "accuracy": 0.9095795131204553, "f1_macro": 0.9047947748023956, "f1_weighted": 0.909791600864584, "precision": 0.9048355690866694, "recall": 0.904972206257656 }
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": "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", "k", "o", "out_proj", "q", "v", "wi", "wo" ]
877,537,933
138,806,912
128
9199.25
5102.5
{ "accuracy": 0.8721150806196649, "f1_macro": 0.8591288491282163, "f1_weighted": 0.872374819498227, "precision": 0.8613691745129466, "recall": 0.8575434288759626 }
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
6541.97
3532.29
{ "accuracy": 0.9015965855200759, "f1_macro": 0.8970336687853184, "f1_weighted": 0.9018458022216244, "precision": 0.8982304900194211, "recall": 0.8961272149557615 }
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
8160.37
2285.03
{ "accuracy": 0.9038887132469174, "f1_macro": 0.899793550023211, "f1_weighted": 0.9041519870656646, "precision": 0.8999880562251698, "recall": 0.8998489571447407 }
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": "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", "k_proj", "out_proj", "q_proj", "v_proj" ]
476,957,325
69,600,896
128
4953.48
2659.18
{ "accuracy": 0.8932184634840341, "f1_macro": 0.8876334553560206, "f1_weighted": 0.8933980793917257, "precision": 0.8886245923826498, "recall": 0.8869163506767225 }
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
8151.75
2261.46
{ "accuracy": 0.9048371798925071, "f1_macro": 0.9011313064774524, "f1_weighted": 0.9050404310641808, "precision": 0.9021499907459358, "recall": 0.9003864301047186 }
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
2686.86
{ "accuracy": 0.8957477078722732, "f1_macro": 0.8908336420875144, "f1_weighted": 0.89600323293089, "precision": 0.8924190564442018, "recall": 0.8895911073887512 }
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": "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", "k_proj", "out_proj", "q_proj", "v_proj" ]
476,955,277
69,600,896
128
4947.9
2604.7
{ "accuracy": 0.8962219411950679, "f1_macro": 0.8916736968085696, "f1_weighted": 0.8965200233897956, "precision": 0.8926225060817129, "recall": 0.8910365893978116 }
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
2210.97
{ "accuracy": 0.8955896300980082, "f1_macro": 0.8910125634203152, "f1_weighted": 0.8957623454439088, "precision": 0.891111273906099, "recall": 0.8910708781970247 }
google/mt5-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", "k", "o", "out_proj", "q", "v", "wi_0", "wi_1", "wo" ]
445,476,237
54,560,384
128
4775.07
2228.44
{ "accuracy": 0.09919380335124882, "f1_macro": 0.06568069861024975, "f1_weighted": 0.07703507652421036, "precision": 0.07782913360585943, "recall": 0.08318972710637867 }
google/mt5-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
390,915,853
390,915,853
null
6318.92
2188.26
{ "accuracy": 0.8661081251975972, "f1_macro": 0.8589544649328975, "f1_weighted": 0.8663063088605754, "precision": 0.8610853372510989, "recall": 0.8574685082494274 }
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
8311.65
3253.41
{ "accuracy": 0.8981979133733797, "f1_macro": 0.8935053836264897, "f1_weighted": 0.8985034298703891, "precision": 0.8935462658157088, "recall": 0.8939206617468962 }
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
7745.19
2136.86
{ "accuracy": 0.8951153967752135, "f1_macro": 0.8898950179684832, "f1_weighted": 0.8955008676131782, "precision": 0.8893089299176236, "recall": 0.8909279042555238 }
google/flan-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": "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", "k", "o", "out_proj", "q", "v", "wi_0", "wi_1", "wo" ]
897,985,165
146,671,232
128
9606.45
5355.02
{ "accuracy": 0.8914796079671198, "f1_macro": 0.8849729790645503, "f1_weighted": 0.8918009512487616, "precision": 0.8851864226743196, "recall": 0.885307579413369 }
google/mt5-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
390,915,853
390,915,853
null
6318.92
2198.71
{ "accuracy": 0.8834966803667405, "f1_macro": 0.8778074539483794, "f1_weighted": 0.8838512210278539, "precision": 0.8774338970909875, "recall": 0.8785832685211372 }
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": null, "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
5841.54
2289.7
{ "accuracy": 0.9046000632311098, "f1_macro": 0.8995189879136327, "f1_weighted": 0.9047133001753334, "precision": 0.899535666284203, "recall": 0.8996826159951664 }
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": "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", "k", "o", "out_proj", "q", "v", "wi_0", "wi_1", "wo" ]
278,064,525
54,560,384
128
3414.4
1892.28
{ "accuracy": 0.8642111919064179, "f1_macro": 0.8488008364795097, "f1_weighted": 0.8636116736586654, "precision": 0.8540781727722316, "recall": 0.8458687676960963 }
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
4528.15
1386.31
{ "accuracy": 0.8862630414163769, "f1_macro": 0.8789790960185098, "f1_weighted": 0.8863287242396712, "precision": 0.8800243113670079, "recall": 0.8782254596018202 }
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": null, "output_dir": "outputs", "report_to": "none", "save_strategy": "no", "save_total_limit": 0, "seed": 3407, "warmup_steps": 5, "weight_decay": 0.01 }
null
355,375,117
355,375,117
null
5240.13
2022.53
{ "accuracy": 0.8799399304457793, "f1_macro": 0.8735354302848027, "f1_weighted": 0.8801174756995317, "precision": 0.8739746184920809, "recall": 0.8733257925176494 }
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
5125.67
1993.92
{ "accuracy": 0.898751185583307, "f1_macro": 0.8951329869378137, "f1_weighted": 0.8989588949748349, "precision": 0.8953322684084845, "recall": 0.895255373984728 }
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": null, "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
4886.3
1979.68
{ "accuracy": 0.8940878912424913, "f1_macro": 0.889435885130686, "f1_weighted": 0.8942596153707378, "precision": 0.8899974719067798, "recall": 0.8891880748342343 }
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": "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", "k", "o", "out_proj", "q", "v", "wi_0", "wi_1", "wo" ]
278,064,525
54,560,384
128
3435.77
1885.23
{ "accuracy": 0.8676889029402466, "f1_macro": 0.853043637287559, "f1_weighted": 0.8670407376042846, "precision": 0.8601355114647885, "recall": 0.84841079245875 }
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
4555.87
2424.85
{ "accuracy": 0.8952734745494784, "f1_macro": 0.8900675235307861, "f1_weighted": 0.8954996948684351, "precision": 0.8897942657947241, "recall": 0.8905441240027205 }
Qwen/Qwen3-Reranker-0.6B
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 }
[ "down_proj", "gate_proj", "k_proj", "o_proj", "q_proj", "score", "up_proj", "v_proj" ]
605,895,680
10,105,856
16
9132.9
1356.39
{ "accuracy": 0.8771735693961429, "f1_macro": 0.8702535525974745, "f1_weighted": 0.8772584775471817, "precision": 0.8724076564785128, "recall": 0.8686663350999541 }
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 }
[ "dense", "key", "out_proj", "query", "value" ]
384,749,594
29,374,477
64
3738.58
5230.46
{ "accuracy": 0.8290388871324692, "f1_macro": 0.8147004214093811, "f1_weighted": 0.8288830652828068, "precision": 0.8184949863990723, "recall": 0.812103590433569 }
Qwen/Qwen3-Reranker-0.6B
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
595,789,824
595,789,824
null
9549.43
2318.11
{ "accuracy": 0.8831805248182105, "f1_macro": 0.8782251691957009, "f1_weighted": 0.8831245877003653, "precision": 0.8791906862468889, "recall": 0.8777928064578825 }
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": null, "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
6600.11
13276.01
{ "accuracy": 0.9043629465697123, "f1_macro": 0.9005021437991989, "f1_weighted": 0.9046015313934022, "precision": 0.9010434353119886, "recall": 0.9002219808456456 }
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": "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", "k", "o", "out_proj", "q", "v", "wi", "wo" ]
808,134,477
69,403,456
64
8199.91
4534.89
{ "accuracy": 0.8572557698387606, "f1_macro": 0.841131480827054, "f1_weighted": 0.8565190700530101, "precision": 0.8495700472020993, "recall": 0.8365779865452315 }
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
9327.92
4961.76
{ "accuracy": 0.9042839076825798, "f1_macro": 0.8994780776201454, "f1_weighted": 0.9044318222434715, "precision": 0.8995062835974748, "recall": 0.899606014266422 }
facebook/opt-350m
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 }
[ "fc1", "fc2", "k_proj", "out_proj", "project_in", "project_out", "q_proj", "score", "v_proj" ]
338,336,768
7,133,696
16
5661.02
1110.03
{ "accuracy": 0.8787543471387923, "f1_macro": 0.8721362284752383, "f1_weighted": 0.8788914650366745, "precision": 0.8731708736787129, "recall": 0.871314860703799 }
facebook/opt-350m
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
331,203,072
331,203,072
null
4733.65
1891.65
{ "accuracy": 0.8942459690167562, "f1_macro": 0.890061218243037, "f1_weighted": 0.8944940419656644, "precision": 0.8917693194136161, "recall": 0.8887628083037556 }
facebook/opt-350m
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 }
[ "fc1", "fc2", "k_proj", "out_proj", "project_in", "project_out", "q_proj", "score", "v_proj" ]
388,226,048
57,022,976
128
5896.18
1100.53
{ "accuracy": 0.8906101802086627, "f1_macro": 0.8858184185254956, "f1_weighted": 0.8908711552279864, "precision": 0.8865243003840713, "recall": 0.8853746299453567 }
AdaLoragoogle/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 }
[ "query", "key", "value" ]
578,605,818
2,670,349
12
1122.46
1428.45
{ "accuracy": 0.7662820107492887, "f1_macro": 0.7183824963621053, "f1_weighted": 0.7551938711716928, "precision": 0.7714909586661263, "recall": 0.7179484368013035 }
AdaLoraanswerdotai/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" ]
453,708,043
57,863,309
128
2699.28
1413.37
{ "accuracy": 0.7409105279797661, "f1_macro": 0.7092834501396117, "f1_weighted": 0.7371817661828275, "precision": 0.7187524389943353, "recall": 0.7063034206904508 }
IA3IA3google/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 }
[ "query", "key", "value", "dense" ]
576,283,290
347,917
128
1500.07
1081.15
{ "accuracy": 0.8187638318052481, "f1_macro": 0.8013335983538513, "f1_weighted": 0.8176602536250689, "precision": 0.8113608305550355, "recall": 0.7958037563136086 }
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": null, "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
6698.0
2282.19
{ "accuracy": 0.9009642744230161, "f1_macro": 0.8974776865926929, "f1_weighted": 0.9011594891203882, "precision": 0.8981514781376804, "recall": 0.897059002258622 }
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": null, "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
11218.02
3368.51
{ "accuracy": 0.1007745810938982, "f1_macro": 0.014084429249217071, "f1_weighted": 0.018451581947974468, "precision": 0.007751890853376784, "recall": 0.07692307692307693 }
IA3albert/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", "key", "pooler", "query", "value" ]
222,743,194
94,349
128
3145.2
5704.41
{ "accuracy": 0.11286753082516598, "f1_macro": 0.0670763630782276, "f1_weighted": 0.08051722070240865, "precision": 0.17353886403475283, "recall": 0.09234471089747195 }
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", "key", "pooler", "query", "value" ]
233,728,538
11,079,693
128
3528.43
6361.86
{ "accuracy": 0.8823901359468859, "f1_macro": 0.8748698970875665, "f1_weighted": 0.8827637400268411, "precision": 0.8765650809706198, "recall": 0.8736846904861518 }
IA3facebook/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", "k_proj", "out_proj", "q_proj", "v_proj" ]
407,626,765
272,384
128
3894.85
2027.25
{ "accuracy": 0.12251027505532722, "f1_macro": 0.06590807606131438, "f1_weighted": 0.07466087784878378, "precision": 0.10856555053186293, "recall": 0.10446177788103327 }
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", "key", "query", "value" ]
392,053,786
56,898,573
128
3966.29
2158.52
{ "accuracy": 0.8820739803983559, "f1_macro": 0.8755758255370101, "f1_weighted": 0.8823030784909592, "precision": 0.8763014850072669, "recall": 0.8751351508448448 }
IA3google-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", "key", "query", "value" ]
335,390,746
235,533
128
3102.02
1694.13
{ "accuracy": 0.12361681947518179, "f1_macro": 0.08176892249117239, "f1_weighted": 0.09535159344680243, "precision": 0.10771644157520274, "recall": 0.10440121934718778 }
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", "key", "query", "value" ]
363,611,162
28,455,949
64
3541.51
1983.49
{ "accuracy": 0.8752766361049636, "f1_macro": 0.8691827130521451, "f1_weighted": 0.875663798667643, "precision": 0.8704954969489104, "recall": 0.8683782605717887 }
IA3microsoft/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" ]
406,461,466
235,533
128
3574.35
2013.82
{ "accuracy": 0.10852039203288018, "f1_macro": 0.03684689621010598, "f1_weighted": 0.04615635640081999, "precision": 0.027029565859150614, "recall": 0.08592691649786904 }
IA3microsoft/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" ]
887,327,258
353,293
128
8034.63
4344.58
{ "accuracy": 0.315365159658552, "f1_macro": 0.2249548774771481, "f1_weighted": 0.2643008780334069, "precision": 0.41948613942483653, "recall": 0.2628803935565058 }
IA3google/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": "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", "k", "o", "out_proj", "q", "v", "wi_0", "wi_1", "wo" ]
223,733,005
228,864
128
2617.15
1328.39
{ "accuracy": 0.11041732532405944, "f1_macro": 0.03180686384808433, "f1_weighted": 0.03996022520732509, "precision": 0.046744560377920526, "recall": 0.08609947390817174 }
IA3google/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" ]
576,283,546
348,173
128
5308.28
2823.91
{ "accuracy": 0.7071609231742018, "f1_macro": 0.6497465714544796, "f1_weighted": 0.6902763211291268, "precision": 0.6734318523007659, "recall": 0.6563470484263196 }
google/flan-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": "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
751,313,933
751,313,933
null
11262.54
4953.5
{ "accuracy": 0.9059437243123617, "f1_macro": 0.9021431761738474, "f1_weighted": 0.9061222093375123, "precision": 0.9027211417639717, "recall": 0.9017820311968541 }
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
11616.96
18421.1
{ "accuracy": 0.1007745810938982, "f1_macro": 0.014084429249217071, "f1_weighted": 0.018451581947974468, "precision": 0.007751890853376784, "recall": 0.07692307692307693 }
README.md exists but content is empty.
Downloads last month
5
Size of downloaded dataset files:
17.3 kB
Size of the auto-converted Parquet files:
17.3 kB
Number of rows:
55