Datasets:
ainewtrend07
/
DecoderLora

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
int64
Memory Allocation
string
Training Time
string
Performance
dict
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
3192.52
1816.04
{ "accuracy": 0.8736958583623142, "f1_macro": 0.867189851837536, "f1_weighted": 0.8738732804844304, "precision": 0.8687124581949315, "recall": 0.8659522973882586 }
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" ]
359,717,888
28,514,816
64
3511.71
1933.9
{ "accuracy": 0.8845241858994626, "f1_macro": 0.8791919666544541, "f1_weighted": 0.8847804587734818, "precision": 0.8803147282468918, "recall": 0.8784517344390299 }
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
3907.75
2094.64
{ "accuracy": 0.889819791337338, "f1_macro": 0.884630711981763, "f1_weighted": 0.8899955959217245, "precision": 0.8854723912755869, "recall": 0.8841072312073395 }
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
3935.12
1745.86
{ "accuracy": 0.8751975972178312, "f1_macro": 0.8676171642677661, "f1_weighted": 0.875420876089299, "precision": 0.8688290909883869, "recall": 0.8667860672509442 }
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" ]
636,173,312
40,383,488
64
4360.05
1839.63
{ "accuracy": 0.8881599747075561, "f1_macro": 0.882864848614931, "f1_weighted": 0.8883364746381752, "precision": 0.8834596635006287, "recall": 0.8825225063931865 }
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" ]
676,543,488
80,753,664
128
5010.25
1969.5
{ "accuracy": 0.891005374644325, "f1_macro": 0.8859257239477754, "f1_weighted": 0.8911926922032317, "precision": 0.8871395813245484, "recall": 0.8850757189032036 }