Datasets:
ainewtrend07
/
EncoderDecoderLora

Dataset card Data Studio Files
xet
Community
Model_name
stringclasses
7 values
Train_size
int64
50.8k
50.8k
Test_size
int64
12.7k
12.7k
arg
dict
lora
listlengths
7
9
Parameters
int64
278M
898M
Trainable_parameters
int64
54.6M
147M
r
int64
128
128
Memory Allocation
stringclasses
7 values
Training Time
stringclasses
7 values
Performance
dict
google-t5/t5-large
50,775
12,652
{ "auto_find_batch_size": true, "gradient_accumulation_steps": 4, "learning_rate": 0.00005, "logging_steps": 1, "lr_scheduler_type": "linear", "num_train_epochs": 1, "optim": "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
4902.33
{ "accuracy": 0.8788333860259248, "f1_macro": 0.8664614548233509, "f1_weighted": 0.8788821788151464, "precision": 0.8697190616327306, "recall": 0.8644016669156487 }
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
4952.94
2560.73
{ "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": "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
4944.89
2521.55
{ "accuracy": 0.8962219411950679, "f1_macro": 0.8916736968085696, "f1_weighted": 0.8965200233897956, "precision": 0.8926225060817129, "recall": 0.8910365893978116 }
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
4755.67
2208.04
{ "accuracy": 0.10014226999683845, "f1_macro": 0.06223054711642854, "f1_weighted": 0.07313441175226931, "precision": 0.07762025226857788, "recall": 0.08399602268916932 }
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
9675.45
5380.46
{ "accuracy": 0.8914796079671198, "f1_macro": 0.8849729790645503, "f1_weighted": 0.8918009512487616, "precision": 0.8851864226743196, "recall": 0.885307579413369 }
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
3417.68
1910.86
{ "accuracy": 0.8642111919064179, "f1_macro": 0.8488008364795097, "f1_weighted": 0.8636116736586654, "precision": 0.8540781727722316, "recall": 0.8458687676960963 }
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", "k_proj", "out_proj", "q_proj", "v_proj" ]
476,955,277
69,600,896
128
4944.95
2548.05
{ "accuracy": 0.8929023079355043, "f1_macro": 0.8877526305367495, "f1_weighted": 0.8931195890604748, "precision": 0.8881425232364214, "recall": 0.8876069519888231 }