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
}
|
README.md exists but content is empty.
- Downloads last month
- 3